Flexibility & Concrete Core Conditioning Synonyms or a contradiction? 15 December 2009 Final Report

Transcription

1 Flexibility & Concrete Core Conditioning Synonyms or a contradiction? 15 December 2009 Final Report

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3 Flexibility & Concrete Core Conditioning Synonyms or a contradiction? Document title Flexibility & Concrete Core Conditioning Synonyms or a contradiction? Program Eindhoven University of Technology Master program Building Services Author Jeroen Rietkerk Studentid Committee members prof. dr. ir. J.L.M. Hensen - TU Eindhoven dr. ir. ing. A.W.M. van Schijndel - TU Eindhoven ir. J.P. Ruchti - Royal Haskoning Graduation company Royal Haskoning Division Building Services - Rotterdam Status Final Report Date 15 December 2009

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5 ABSTRACT The building design process is a complex process where specialists of different design disciplines work together to realize a building that satisfies the design objectives of the project. Nowadays, these design objectives are more and more determined by sustainability, flexibility and the quality of the indoor environment. The realization of the current design objectives requires the integration of new installation concepts within the building design. A potential concept is the application of Concrete Core Conditioning. Concrete Core Conditioning is a system for the thermal conditioning of buildings and uses water carrying pipes for heating and cooling which are embedded in the centre of the floor/ ceiling construction. It is known as an alternative for conventional installation concepts to reduce the energy consumption and increase the thermal comfort. However, literature doesn t give insight in the behaviour of Concrete Core Conditioning in relation to the changing utilization of a building and with regard to thermal comfort. The objective of this thesis is to gain insight in the influence of building and utilization parameters on the behaviour of Concrete Core Conditioning systems in relation to the indoor thermal comfort. This in order to answer the main research question of the thesis: What are the consequences of applying Concrete Core Conditioning systems for the flexibility of a building concept, now and in the future, and how could this flexibility be increased? The behaviour of Concrete Core Conditioning has been researched with the use of a simulation model. This simulation model has been developed within the software environment of Matlab/ Simulink. The developed building simulation model concerns the integration of a developed Concrete Core Conditioning model into the model HamBase which can simulate the indoor temperatures, relative humidity and energy consumption of a multi-zone building. On basis of a case study 8 different simulation scenarios were formulated with regard to building flexibility. The results of these performed simulation scenarios were evaluated with a performance indicator for thermal comfort, thermal power and energy consumption. The researched flexibility concerns the technical flexibility of a building. This flexibility influences several building and utilization properties which affect the thermal comfort in a zone. The simulation scenarios are based on these properties and resulted in the following input parameters with regard to flexibility: orientation, location within building (horizontal and vertical), zone geometry, sun entrance, construction mass, internal heat gains and supply air volume. General thermal comfort is standardized by PMV values in the ISO These PMV values were converted into operative temperature ranges that are directly related to the outdoor temperature. This makes these operative temperature ranges suitable to evaluate the thermal comfort throughout a whole year and, therefore, were used to evaluate the thermal comfort of the simulation results. A sensitivity analysis of the simulation results shows that the thermal comfort in a zone is sensitive for changes in all flexibility parameters, but the size of this influence differs for each parameter. Table I presents the ranking of the influence of each of the parameters on the thermal comfort in a zone, including the parameter values which has the potential to realize the best achievable thermal comfort. - i -

6 Ranking Flexibility parameter Best option (potentially) with regard to thermal comfort 1 location horizontal internal 2 internal heat gains 35 W/ m 2 3 geometry medium, large 4 sun entrance construction mass high 6 facade orientation North 7 supply air volume 2 ACH 4 ACH 8 location vertical top floor Table I: Overview of potential best values for each of the flexibility parameters with regard to the realization of the best achievable indoor thermal comfort. The flexibility parameters are ranked from most to least influencing parameter and count for the selected reference situation and boundary conditions as described in Concrete Core Conditioning has the ability to adapt its thermal power to the thermal conditions in the zone. This self control ability of Concrete Conditioning is not appropriate to adapt its thermal power to every possible situation in relation to flexibility. The use of an additional installation component, e.g. a convector unit, makes it possible to realize and maintain the desired indoor temperature actively. Concrete Core Conditioning can be used in flexible building concepts, but requires the application of an additional installation component for the supply of cooling and heating power. The combination of Concrete Core Conditioning and an additional installation component result in a climate system that is suitable to accommodate changes in the working environment without loss of thermal comfort. This system result in an increase of the energy consumption, but its applicability in combination with renewable energy sources lets this system still have the potential to be an energy efficient climate system. - ii -

7 ACKNOWLEDGEMENTS This report is the result of my final project for the Master s degree program in Building Services at the Eindhoven University of Technology. I started this Master s degree program in September 2003 as a dual student which means that I combined this program with my work at Royal Haskoning. This made it important for me to select a subject for my thesis that fitted with my motivated interest in modelling together with the interest of Royal Haskoning. This combination was found in the subject Concrete Core Conditioning and its behaviour in relation to building flexibility. The thesis from start to finalization took me 2,5 years. A period in which I learned about Concrete Core Conditioning, but as even important, I learned very much about the processes that take place within a project like these: the structure of scientific research, contacts with different kind of people and dealing with different opinions or suggestions of my advisors. During this process I did a lot of work, but this wasn t possible without the support I got. At first I want to thank the members of my graduation committee. From the Eindhoven University of Technology these are Jan Hensen en Jos van Schijndel. I want to thank Jos, because his practical view and suggestions helped me to keep me motivated to continue my thesis. I want to thank Jan, because of his critical view about the right use of terminology and, more important, giving me insight in the process of scientific research. Finally, I want to thank Hans Ruchti of Royal Haskoning. Hans supported me very well in giving me feedback and he always had time to discuss my progress which helped me really to manage the process. The progress presentations at the Eindhoven University of Technology, in presence of the MSc and PhD students, were very useful, because of the feedback I got there. Especially, I want to thank Marija Trcka for her good suggestions about modelling. Also I want to thank Christian Struck for his feedback about sensitivity and uncertainty analysis and helping me with getting the right literature about it. Finally, I want to thank my family and friends for their support during this exciting period, but also for the enjoyable time we spent together which helped me to take my mind off things. Especially, I want to thank my parents, because they supported me very well, even during a time that has not always been easy for them. Jeroen Rietkerk December iii -

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9 NOMENCLATURE Symbol Description Unit δ outside pipe diameter m ε 1 emissivity of construction surface - ε 2 emissivity of surrounding construction surfaces - λ thermal conductivity W/ m K ρ density kg/ m 3 σ Stefan-Boltzmann constant (= 5, ) W/ m 2 K 4 λ thermal conductivity of construction layer with CCC W/ m K d pipe spacing m A surface area m 2 A floor/ceiling surface area of floor/ ceiling m 2 A wall surface area of the walls m 2 C thermal capacitance J/ K c specific heat J/ kg K D c layer thickness m G plant vapour flow released in zone kg/ s h heat transfer coefficient (radiant + convective part) W/ m 2 K h cv convective heat transfer coefficient W/ m 2 K h e_ground heat transfer coefficient at ground side of ground floor W/ m 2 K (standard: 25 W/m 2 K (rad+cv)) h e_roof heat transfer coefficient at roof side of roof W/ m 2 K (standard: 25 W/m 2 K (rad+cv)) h rad radiant heat transfer coefficient W/ m 2 K m ahu_cc mixing rate between outdoor air conditions and conditions on - the surface of the cooling coil m w water mass flow kg/ s p e total outdoor pressure (= ) Pa p w_e partial pressure of water vapour of outdoor air Pa p ws_ahu_cc water vapour saturation pressure on cooling coil surface Pa q solar_e solar radiation on horizontal outdoor surface W/ m 2 q solar_i solar heat released in zone W/ m 2 Q energy consumption kwh R thermal resistance K R cv convective heat transfer resistance K/ W RH e outdoor relative humidity - R rad radiant heat transfer resistance K/ W R x thermal resistance between pipe and centre construction layer K/ W t time s T ahu_cc_mean mean surface temperature of cooling coil C T air air temperature T air_supply supply air temperature C T c construction temperature C T cs surface temperature of construction of layer C T e outdoor temperature C T e_ground outdoor temperature at ground side C T mrt mean radiant temperature (unit K in case of calculation of radiant heat transfer coefficient) C (or K) operative temperature T op - v -

10 T w_in water inlet temperature C T w_out water outlet temperature C T wall mean wall temperature C V volume m 3 V supply_air supply air volume m 3 / h x ahu_cc absolute humidity on surface of cooling coil kg/ kg x ahu_cc_out absolute humidity of supply air after cooling coil kg/ kg x ahu_hc_out absolute humidity of supply air after heating coil kg/ kg x e absolute humidity of outdoor air kg/ kg Φ ahu_cc cooling power of AHU to cool supply air W Φ ahu_cc_lat latent part of cooling power of AHU W Φ ahu_cc_sen sensible part of cooling power of AHU W Φ ahu_central_total power of AHU to heat or cool supply air of all zones W Φ ahu_central_zone power of AHU to heat or cool supply air of 1 zone W Φ ahu_central_zone local heating/ cooling power of supply air W Φ ahu_hc heating power of AHU to heat supply air W Φ ccc_ceiling heating power of ceiling side of construction W Φ ccc_floor heating power of floor side of construction W Φ ccc_total heating power as sum of ceiling and floor side of construction W Φ ccc_water water sided heating power of CCC system W Φ in_i heat flow of system I released in zone W Φ in_ii heat flow of system II released in zone W Φ IHG total internal heat gains W Φ equipment internal heat gains by equipment W Φ lighting internal heat gains by lighting W Φ persons internal heat gains by persons W Φ solar_i solar heat released in zone W Φ supply_air local heating cooling power of supply air W Indices Description i indoor condition ce ceiling side of construction fl floor side of construction gf ground floor side of construction rf roof side of construction 1 2 number of room or construction layer 3 4 number of construction layer w water Abbreviations CCC HTC PMV Concrete Core Conditioning Heat Transfer Coefficient Predicted Mean Vote - vi -

11 CONTENTS Page ABSTRACT ACKNOWLEDGEMENTS NOMENCLATURE I III V 1 INTRODUCTION Background Objective Research questions Methodology Literature analysis Modelling The simulations Outline of the thesis 4 2 LITERATURE ANALYSIS Concrete Core Conditioning Systems Principle Characteristic properties Control strategies Boundary conditions for facade quality Flexibility of a building Methods of flexibility Flexibility related to utilization and building parameters The indoor environment Thermal comfort The operative temperature as performance indicator Sensitivity and uncertainty analysis Uncertainty versus sensitivity Sources for uncertainty Techniques for sensitivity and uncertainty analysis 21 3 MODELLING Modelling the systems Multi-zone building system The Concrete Core Conditioning system Heating, Ventilation and Air Conditioning system System for Heat Transfer Coefficients The CCC building simulation model The complete model Data output Simulation automation 41 4 METHOD TO EVALUATE BEHAVIOUR CONCRETE CORE CONDITIONING Method 43 - vii -

12 4.2 Case study Input parameters Boundary conditions Simulation scenario s Performance indicators Thermal comfort Thermal power Energy consumption Sensitivity analysis 49 5 SIMULATIONS WITH CONCRETE CORE CONDITIONING Results: self control strategy of indoor temperature Reference situation Scenario 1: orientation of facade Scenario 2: location within building horizontal Scenario 3: location within building vertical Scenario 4: geometry of room Scenario 5: sun entrance Scenario 6: construction mass Scenario 7: internal heat gains Scenario 8: supply air volume Results: active control strategy of indoor temperature Thermal comfort Thermal power Energy consumption Sensitivity analysis Overall results Selection of favourable input parameters 71 6 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS Discussion Conclusions Recommendations 77 7 REFERENCES 79 - viii -

13 ANNEX The following appendices are part of this report: Annex A Annex B Annex C Annex D Annex E Annex F Annex G Annex H Annex I Annex J Annex K Annex L Annex M Standard based design criteria for the thermal environment Methods to evaluate thermal comfort conditions Operative temperature equivalents of standardized PMV values Modifications to the multi zone model HamBase Modelling Concrete Core Conditioning Modelling HVAC system Modelling HTC system The CCC building simulation model: starting guide Simulation parameters & boundary conditions Calculation of input parameter values Simulation results: first set Matlab code: Modified HamBase M-files Matlab code: S-function Concrete Core Conditioning system Separately, a CD with the following digital information is part of this report: This report in digital format; Simulation models of systems: HamBase: The original version, dated October 2006; The modified version; Concrete Core Conditioning The original version, dated September 2009; The version used for verification; HVAC The original version; The version used for verification; Heat Transfer Coefficient The original version; The version used for verification; The CCC building simulation model: The basis model; The basis model used to run simulation series programmatically; The basis model with an active control of indoor temperature. - ix -

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15 1 INTRODUCTION This chapter describes the background, objective, research questions and method of this thesis. 1.1 Background The building design process can be characterized as a complex process where specialists of different design disciplines work together to realize a building that satisfies the design objectives of the project. Design objectives change over time, because of changes in society, technical progress and changing needs of building occupants. Nowadays, there is an increasing attention for sustainability, flexibility and the quality of the indoor environment. Films like An inconvenient truth of Al Gore increase the public awareness of the necessity of a sustainable environment. In this environment ecological pressure will be decreased by making an efficient use of natural resources instead of wasting them by overconsumption. An important aspect of sustainability is the reduction of CO 2 emissions, because these emissions contribute most to global warming. Carbon dioxide is emitted by the largescale burning of non-renewable energy sources (coal, natural gas and oil) for the production of electricity and traffic. The global insight for the need of reducing CO 2 emissions resulted in global agreements. These agreements established an emission reduce for the Netherlands of 6% (CO 2 equivalents) [VROM, 2009] for the period In the Netherlands the built environment is responsible for about 35% of the total energy consumption [ECN, 2009] and in 2005 the building sector was responsible for 39% of the waste deposit [SenterNovem, 2008]. Therefore, the built environment has a great potential to increase the sustainability of the environment. Organisation structures are changing continuously. These changes result in changing requirements for the working environment and these should be accommodated by the building. Buildings with technical flexibility have the possibility to change the function and lay out of the building and its installations [IFD, 2009]. Due to flexibility the buildings can be adapted to changing organization structures and this makes the building longer suitable for the owner. Besides, flexibility increases the sustainability of a building by lengthen its lifetime [IFD, 2009]. The well being of building occupants has a direct relationship with the quality of the indoor environment. This quality concerns the air quality, thermal, visual and acoustic comfort. The quality of the indoor environment influences the health and comfort of employees and with that the productivity and absence because of illness. A qualitative good indoor environment can increase the productivity of employees with 10 to 15% [Boerstra, 2003]. Aspects that contribute significantly to the quality of the indoor environment are indoor temperature, fresh air volume, personal influence and air pollution. Research proves that an indoor temperature above neutral (24 25 C) results in a productivity decrease of 3 to 7% per C. Increasing the ventilation rate per person (more than 30 à 40 m 3 / h per person) results in a productivity increase of 1 or 2%, but removing air polluters is far more effective (productivity increase of 1 7%). Besides, the possibility of individual influence of the indoor temperature can result in a productivity increase of 3% [Boerstra, 2003]

16 The relationship between the energy efficiency of a building and the health of building occupants is at random. Therefore, the philosophy that a good indoor environment results in a higher energy use is a misunderstanding. With a well thought-out building design health and energy efficiency can go well together [Boerstra, 2006]. Concrete Core Conditioning Systems The integration of new installation concepts within the building design can reduce the energy consumption of the built environment together with an increasing quality of the indoor environment. A potential concept is the application of Concrete Core Conditioning systems. Concrete Core Conditioning is a relatively new installation concept for heating and cooling of buildings. Since the introduction in the early nineties (Switzerland) the application has emerged as an energy efficient and cost effective concept which realizes a good thermal indoor environment [Lehmann, 2007]. The basic principle of a Concrete Core Conditioning system is the application of a water carrying piping system for heating and cooling that is embedded in the centre of the floor/ ceiling construction. Due to the location of the piping system the building mass will be thermally activated. This thermal activation results in the storage of thermal energy in the building construction (floor/ ceiling) that is used for room cooling and heating. For the heat exchange between the surface and zone relatively small temperature differences are required and this allows water temperatures close to the zone temperature. This make the Concrete Core Conditioning systems suitable for energy efficient heating and cooling generators. In the Netherlands Concrete Core Conditioning systems are gaining popularity as application for the thermal conditioning of offices and schools. The system is known as an alternative for conventional installation concepts to reduce the energy consumption and increase the indoor thermal comfort. However, the behaviour of Concrete Core Conditioning systems in relation to the changing utilization of a building, with regard to thermal comfort, is unknown. 1.2 Objective The first objective of this thesis is: Gain insight in the influence of building and utilization parameters on the behaviour of Concrete Core Conditioning systems in relation to the thermal comfort in buildings. Based on literature, it s to be expected that Concrete Core Conditioning systems can t provide a good indoor thermal comfort for all varieties and combinations of building and utilization parameters. Therefore, the second objective of this thesis is: Gain insight in how additional installation components could widen the application range of Concrete Core Conditioning systems with respect to the thermal comfort

17 1.3 Research questions The main question of the thesis is: What are the consequences of applying Concrete Core Conditioning systems for the flexibility of a building concept, now and in the future, and how could this flexibility be increased? To answer the main question of the thesis a number of sub questions have been formulated: Which aspects represent flexibility? What are the allowed indoor thermal comfort ranges? To what extent flexibility parameters influence the behaviour of Concrete Core Conditioning systems with regard to the indoor thermal comfort? 1.4 Methodology To achieve the objectives of the thesis a dynamic simulation model of a Concrete Core Conditioning system has been developed. This model is used to research the behaviour of the Concrete Core Conditioning system with regard to the objectives and research questions of the thesis. The method used to perform this research has been divided into several phases with each its specific activities. The contents of each phase are described in the following paragraphs Literature analysis Modelling A literature review started the first phase of the thesis. This review gained insight in the background, known characteristics and properties of Concrete Core Conditioning systems. Furthermore, it is important to define flexibility to outline the thesis, because flexibility is a key element in the main question of the thesis. Based on literature a definition of flexibility has been formulated. This formulation describes the aspects that are related to flexibility, including a specification of the parameters it concerns. Finally, methods to evaluate the indoor thermal comfort have been discussed to decide which method should be used as performance indicator for the simulations. Also methods for sensitivity analysis are evaluated, because a sensitivity analysis is needed to evaluate the sensitivity of the performance indicator for parameters. In the second phase the building of the dynamic simulation model of the Concrete Core Conditioning system takes place in the software environment of Matlab/ Simulink. The chosen in-/ output structure of the model makes it possible to connect the model to a building simulation model. For this research has been chosen for a connection with the HamBase model of the Eindhoven University of Technology (TU/e). This model simulates the heat and vapour flows within multi zone buildings. The HamBase model is validated, but the model of the Concrete Core Conditioning system is only manually verified, because measurements of complex Concrete Core Conditioning systems are outside the scope of this thesis

18 1.4.3 The simulations In the third phase the Concrete Core Conditioning building simulation model was used to make simulations to evaluate the behaviour of Concrete Core Conditioning. The behaviour has been evaluated by the performance indicators for indoor thermal comfort, thermal power and energy consumption. Furthermore, a sensitivity analysis has been performed to assess the sensitivity of the simulation output for changes in the input parameters. The first set of simulations was used to gain insight in the influence of the flexibility parameters on the behaviour of the Concrete Core Conditioning system. From these simulations results conclusions have been drawn about the application range of the solely use Concrete Core Conditioning systems in relation to flexibility. The second set of simulations was used to gain insight in how the application range of Concrete Core Conditioning systems could possibly be widened with the application of additional installation components. The results of al performed simulations together, were used to define conclusions about the potential of the Concrete Core Conditioning system in relation to flexibility. 1.5 Outline of the thesis According to the methodology the report starts in chapter 2 with the literature analysis. Successively, chapter 3 describes the modelling of the Concrete Core Conditioning building simulation model. Chapter 4 describes the method used to evaluate the behaviour of Concrete Core Conditioning in relation to flexibility. At first the case study is introduced on basis the simulation scenarios were defined that were used to perform simulations with the CCC building simulation model. Successively, the performance indicators are described which were used to evaluate the simulation results. The results of each of the performed simulations, including the overall results, are described in chapter 5. Chapter 6 starts with the discussion which describes some comments with regard to the used methodology. Successively, the conclusions are formulated which answer the research questions of this thesis. The report ends with recommendations for improvement or further research

19 2 LITERATURE ANALYSIS This chapter describes the information relevant for this thesis on basis of literature. The first paragraph is about the background, known characteristics and properties of Concrete Core Conditioning. Successively, flexibility is described with regard to buildings and the objective of this thesis. The third paragraph gives insight in criteria for the indoor thermal comfort and methods to evaluate this thermal comfort. Finally, the last paragraph describes the methods that can be used to evaluate the sensitivity and uncertainty of a building simulation model s output. 2.1 Concrete Core Conditioning Systems The Romans already knew the function of the building structure within the thermal conditioning strategy of buildings. The thermal storage capacity of the building mass can be used to heat or cool buildings. Already, every building uses its building mass to interact passively with the indoor thermal climate. Nowadays, an active interaction, like the Romans already did (figure 2.1 & 2.2), is also possible Principle Hypocaust: an ancient Roman system of central heating that used hot air from furnaces to heat private houses or baths. The smoke circulated through the enclosed spaces under the floors and between the walls. Figure 2.1: Schematic view of hypocaust. 2 Figure 2.2: Ruins of hypocaust floor at Bognor Roman Villa. 1 In the last decades there has been a growing recognition for energy efficiency and thermal comfort. This resulted in an increasing quality of the thermal insulation of building facades which made it possible to use the building construction for both heating and cooling. Initially, only surface systems were applied, like floor heating and cooling systems [Olesen, 2004]. In the early nineties in Switzerland [Olesen, 2004], however, thermally activated building systems were introduced that uses the thermal storage capacity of the building construction actively. These systems, known as Concrete Core Conditioning, have emerged as an energy efficient and cost effective concept which realizes a good thermal indoor environment [Lehmann, 2007]. Concrete Core Conditioning (CCC) uses the heat storage capacity of the building mass to heat or cool the spaces of a building. To make use of the heat storage capacity the building mass is thermally activated by water carrying pipes that are embedded in the centre of the building construction. The application of the water carrying pipes in the centre of the building construction makes the thermal activation of the whole construction possible and this distinguishes CCC from surface systems (figure 2.3)

20 Concrete Core Conditioning Floor heating Radiant cooling ceiling Figure 2.3: Concrete Core Conditioning activates the complete floor construction, whereas a floor heating system is disconnected from the thermal mass and a radiant cooling ceiling only activates the bottom layer of the construction. The piping system transports heated or cooled water to realize a change of the surface temperature of the building construction. This temperature change results in a temperature difference between the surface and room temperature that is the driving force behind the heat exchange between space and building construction (figure 2.4). The temperature difference between the surfaces and space are relatively small [Olesen, 2002], so the surface temperature of the building construction is heated up or cooled down just a few degrees in relation to the desired room temperature. This results in a heat exchange by means of convection and radiation (figure 2.4). Figure 2.4: Concrete Core Conditioning: heating and cooling with the floor and ceiling by means of radiation and convection. The heat storage capacity of the activated building mass is used as a buffer between the production and use of thermal energy. The effects of the activated building mass as thermal buffer are: It flattens out temperature changes within the spaces (figure 2.5) and this reduces the peaks of the minimum and maximum room temperatures; It prevents an upswing of the indoor temperature in summer period (figure 2.5) [Lehmann, 2007; Schrevel, 2002]]; It detaches the production of heating and cooling energy from the time it is really demanded. Therefore, the buffer capacity result in a decrease of the required peak load and makes it possible to transfer a part of the heat load outside the time of occupancy

21 Figure 2.5: Effect of thermal storage capacity in summer situation [Bruggema, 2007; Lehmann, 20070]. Left: Without CCC the room temperature increases rapidly to a relatively high maximum and the night ventilation isn t sufficient, so the starting temperatures will increase the next warm days. Right: CCC results in a lower maximum room temperature and the CCC is capable to realize the same starting temperature every next warm day Characteristic properties Concrete Core Core Conditioning has some characteristic properties. An outline of these properties is described in this paragraph. Comfort The operative temperature is a parameter to describe the thermal comfort and is the average value of the air and radiant temperature. Several guidelines and standards (e.g. [ISO 7730, 2005]) give a definition of the permissible operative temperature ranges. More information about thermal comfort is described in 2.3. With Concrete Core Conditioning the complete floor and ceiling surface take part in the heat exchange process. With just a small temperature difference between the construction and the space it results in an even distribution of the exchanged heat within the space. The heat exchange between the construction and the space results in a change of both the air and radiant temperature. However, the largest part of the thermal heat is exchanged by means of radiation. Taking into consideration the definition of the operative temperature it means that, in contrast to convective systems, the application of CCC requires air temperatures that are closer to the operative temperature. This means that higher air temperatures in summer and lower air temperatures in winter are allowed to realize an equal operative room temperature. Therefore, Concrete Core Conditioning, which exchanges heat mainly by radiation, has the following advantages with regard to the thermal comfort in a room: The use of both the ceiling and floor results in a lower vertical temperature difference. This decreases the local discomfort due to vertical temperature difference [Buitenhuis, 2007]; - 7 -

22 Lower air temperatures in winter are experienced positively by the occupants. Due to the lower temperature the air has a high relative humidity that reduces the possibility of dehydration of the respiratory tract [Schrevel, 2002]; A reduction of the draught risk, because: Ventilation air can be supplied with a temperature close to the operative temperature [Schrevel, 2002]; The main part of the heat is exchanged by means of radiation and there is just a small temperature difference between construction and space. This reduces the appearance of convective air flows to a minimum [Buitenhuis, 2007]. The application of Concrete Core Conditioning also has some disadvantages. Therefore, attention is needed for the following aspects to avoid discomfort of the occupants: The dynamic behaviour makes an individual control strategy of Concrete Core Conditioning impossible (see item Dynamic thermal behaviour ). To avoid complaints about under cooling the application of additional, local, heating components should be done well considered [Eijdems, 2007]; With Concrete Core Conditioning the application of suspended ceilings is limited (see 2.1.3) and means alternative measures are needed to realise a same amount of sound absorption [Cauberg, 2003]. The selection of the amount and type of these alternatives should be done well considered to make the occupants feel comfortable with the look of these materials and its sound reduction effects. Thermal power The thermal power of Concrete Core Conditioning depends on several aspects. These aspects are the size of the surfaces, the heat transfer coefficients between the construction surfaces and space, the allowable surface temperatures, the heat storage capacity of the construction and the layout of the piping system. The heat transfer coefficient consists of 2 components, namely a radiant and convective component. The heat transfer between the construction surface and the radiant room temperature is represented by the radiant component and the heat transfer between the construction surface and the air temperature is represented by the convective component (figure 2.6). Figure 2.6: Heat transfer coefficient consists of a convective and radiant part. Searching through literature does not bring an unambiguous value of the heat transfer coefficients that should be used when Concrete Core Conditioning is applied. Most obvious is that literature, with regard to Concrete Core Conditioning, often describes a heat transfer coefficient that represents the sum of the convective and radiant - 8 -

23 component. As a result, literature brings out a variety of values that can be used for the representation of the heat transfer coefficient (see table 2.1). Construction Heat Transfer Coefficients (sum of convective and radiant component) Heating Cooling [Bruggema, 2007] [Olesen, 2004] [Weitzmann, 2005] [Bruggema, 2007] [Olesen, 2004] [W/ m 2 K] [W/ m 2 K] [W/ m 2 K] [W/ m 2 K] [W/ m 2 K] floor 8,1 11 0,9 5,6 7 ceiling 5,7 6 5, Table 2.1: Overview of literature based heat transfer coefficients for Concrete Core Conditioning. Standards describe several categories for the environment conditions that occupants accept for general thermal comfort and local discomfort (see also 2.3). Based on the standard [0] the acceptable operative temperature range in winter is 21 C 23 C and in summer 23,5 C 25,5 C. These ranges belong to the highest comfort category A. Based on this category also the minimum and maximum surface temperature can be determined. Where the standard describes a minimum floor temperature of 19 C, it is recommended to use a minimum temperature of 20 C for sedentary activities [Olesen, 2004]. The minimum ceiling temperature is restricted to 17 C, because of the condensation risk. These requirements are shown in table 2.2. Construction Room temperature Surface temperature Thermal power winter summer min max heating cooling (operative) (operative) min max min max [ C] [ C] [ C] [ C] [W/ m 2 ] [W/ m 2 ] [W/ m 2 ] [W/ m 2 ] floor ,8 88 5,9 45, ,5 ceiling , ,3 93,5 Sum of floor and ceiling ,2 139 Table 2.2: Overview of thermal power based on heat transfer coefficients of table 2.1. Based on the environment requirements with regard to thermal comfort, the possible capacities of the Concrete Core Conditioning can be determined on basis of the literature based heat transfer coefficients of table 2.1. These calculated capacities, as shown in table 2.2 and based on the minimum and maximum allowable temperature, shows that the total heating power of Concrete Core Conditioning can vary between 99 to 124 W/ m 2 and the cooling power between 55,2 to 139 W/ m 2. This is a wide range, where even other publications [Buitenhuis, 2007] describe that the total heating power of Concrete Core Conditioning is about 45 W/ m 2 and the cooling power about 40 W/ m 2. The results of table 2.2 show that the choice of a literature based heat transfer coefficient has a great effect on the size of the thermal power. Besides, these literature based heat transfer coefficients are a combination of the radiant and convective heat transfer components. However, it should be taken into account that Concrete Core Conditioning is an active surface system that actively affects the surface temperature of the construction. To cancel out the uncertainty of the selection of a literature based heat transfer coefficient and take into account that Concrete Core Conditioning is an active surface system, the radiant and convective heat transfer coefficients should be calculated separately. To calculate the radiant and convective heat transfer coefficients the following relationships can be used: - 9 -

24 Radiant heat transfer coefficient The radiant heat transfer coefficient is found from [Bruggema, 2007]: h = 4 [1] where: h rad : radiant heat transfer coefficient [W/ m 2 K] ε 1 : emissivity of construction surface [ - ] ε 2 : emissivity of surrounding construction surfaces [ - ] σ : Stefan-Boltzmann constant (5, ) [W/ m 2 K 4 ] T mrt : mean radiant temperature [K] Convective heat transfer coefficient The convective heat transfer coefficient is found from [Recknagel, 2005]: Downward convection 5 h = 04, [2] Upward convection 5 h =, [3] where: h cv : convective heat transfer coefficient ΔT : temperature difference between construction surface and room air temperature [W/ m 2 K] [K] Heat storage capacity The heat transfer coefficients determine the size of the heat flux of the heat exchange between the construction and space. However, the amount of heat that can be exchanged between the construction and the space is determined by the heat storage capacity of the construction. The heat stored in the construction is used to condition the space by the absorption or emission of heat to or from the space. A typical temperature development throughout the day for a summer period is given in figure 2.7. Figure 2.7: Typical temperature cycle with the application of Concrete Core Conditioning [Lehmann, 2007]. The figure shows that the heat gains (internal gains and solar radiation) cause a temperature rise of both the air and operative temperature. The convective part of the heat gains accounts for the greatest part of this temperature rise. The use of the storage capacity allows the absorption of thermal heat and results in a relatively small increase of the surface temperature of the construction

25 To calculate the heat storage capacity of a construction the following relationship can be used: = [5] 55 where: B : heat storage capacity of construction [Wh/ m 2 K] c : specific heat [J/ kg K] ρ : density [kg/ m 3 ] D c : thickness of construction layer [m] Based on this relationship the amount of stored heat that can be effectively used is restricted by: The material properties (specific heat and density) of the construction; The thickness of the construction layer that takes part in the heat exchange; The allowable rise of the room temperature. From practise it is known that only the first ten centimetres of the construction takes part in the heat exchange process [Schrevel, 2002]. This means that the effective heat storage capacity is restricted to the first 10 centimetres of the construction on both the ceiling and floor side. To maintain the same heat flux between the construction and space it means that the variation of the room temperature should be equal to the change of the surface temperature. However, the variation of the room temperature is restricted by the allowable temperature drifts and minimum and maximum room temperatures according to the standards. This means the use of the stored heat is restricted by the indoor temperature requirements. Available surface area The total power that is available for the thermal conditioning of the space is restricted by the available surface of the thermally activated building constructions. This means: An increase of the total thermal power is restricted by the maximum feasible power per square meter activated building construction; The obstruction of the direct contact between the construction and space should be as less as possible. It means that suspended ceilings, which are normally used for acoustic control, cannot be applied. Therefore, alternatives are needed to realize the same amount of sound absorption. A possible alternative is the application of suspended panels with sound absorbing materials on both sides and a size of ca. 40% of the ceiling surface [Cauberg, 2003]. Within these panels lighting can also be integrated. Piping system The thermal power and storage capacity of Concrete Core Conditioning depends on the layout of the piping system. Parameters of this system are: The pipe spacing; The pipe diameter; The vertical position of the pipe level within the construction. It is known that these parameters influence the heat response characteristics [Kobayashi, 2003], but the effect of these parameters on the thermal power

26 and storage capacity is underexposed in literature. Dynamic thermal behaviour The properties of Concrete Core Conditioning result in a characteristic dynamic thermal behaviour. The characteristic aspects of this behaviour are: Self control The heat exchange depends on the relatively small temperature difference between the construction and space. This results in a significant degree of self control [Lehmann, 2007], because the heat flux is influenced by the changing room temperature that goes together with the changing heat load in the room. Thermal slowness Due to its storage capacity, the thermal construction is thermally slow. This means that the surface temperature of the construction cannot be changed rapidly to comply with changing heat loads in the room. Therefore, just small temperature variations of the surface temperature are allowed to prevent discomfort by the under cooling or overheating of a space [Bruggema, 2007]. Energy efficiency Concrete Core Conditioning operates with water temperatures around the room temperature, because the surface temperature of the construction should be around this level. This makes the system suitable for high efficient heating and cooling sources, like heat pumps and ground heat exchangers. Furthermore, the heat storage capacity can reduce the required power of the heating and cooling sources, because a part of the heat load can be transferred to a time outside the occupancy. This can result in a reduction of the required power of the cooling sources with 14% to 50% [Rijksen, 2007]. The combination of the preceding aspects can make Concrete Core Conditioning an energy efficient system that has potential to reduce the energy consumption Control strategies Concrete Core Conditioning is controlled by its supply water temperature. The type of control strategy influences the performance of the system with regard to energy consumption and thermal comfort. To control the water temperature several strategies are possible, but it has to be taken into account that: A strategy that reacts on fast changing heat loads isn t useful, because of the thermal slowness of the system; To make use of the self control ability, the surface temperature of the construction should be around the room temperature. Control strategy Description Water temperature Controls the supply water temperature on basis of a constant value or a certain relationship. Operation time of circulation pump The operation time of the circulation pump will be reduced on basis of the available storage capacity of the construction. Dead-band for room temperature The circulation pump will not be in operation if the room temperature is within a certain temperature range. Use of weather forecast Control the supply water temperature on basis of the weather forecast. Table 2.3: Possible control strategies for Concrete Core Conditioning [Lehmann, 2007; Olesen, 2004]

27 Concrete Core Conditioning can be controlled by using the strategies as mentioned in table 2.3. For the control strategies count [Olesen, 2002; Olesen, 2004; Sommer, 2002]: Water temperatures shouldn t be too low or too high, because it results in undercooling or overheating due to the dynamic behaviour of the system; The largest cooling power can be realized if the water temperature is controlled by the dew point in the space. However, it doesn t have a really good performance, because it results in undercooling and a higher energy consumption, because the space should be reheated; The best performance with regard to energy consumption and thermal comfort can be obtained if the supply water temperature is controlled as a function of the outside temperature. Individual control Concrete Core Conditioning cannot be controlled for each space individually, but its self control ability adapts the heat exchange for each space individually. However, within a building several zones can be determined that have a specific heat load, based on their orientation or specific function. For these zones it can be possible to divide the piping system into some separate zones. For these zones an individual control strategy can be used that takes into account the specific function or orientation of the zone Boundary conditions for facade quality Because the thermal power of Concrete Core Conditioning is restricted, boundary conditions for the quality of the facade are recommended in order to realize a good thermal comfort. An optimum use of the available thermal power and the self control ability is necessary to realize a good indoor temperature. Therefore, external heat loads and heat losses should be reduced. This means for the winter situation a good thermal insulation of the facade and in summer a reduction of the sun entrance. Another aspect that has to be taken into account is the loss of comfort due to draught, because heating appliances in front of the facade will not be used in combination with Concrete Core Conditioning. Draught can be a result of infiltration, but in the area along the facade cold air down draught can also be possible. There is no risk of discomfort due to cold air drown draught if the U-value is lower than 1,5 W/ m 2 K and the window is not taller than 2,7 m [Olesen, 2002]. Larger U-values or taller windows are possible, but requires a zone directly along the facade (1 meter) that is heated up to a maximum floor temperature of 35 C. This reduces the air velocity, which causes the draught, with up to 30% [0]. Therefore, the following properties of the facade are recommended: Insulation Facade : 3,0 m 2 K/ W Glazing : 1,2 W/ m 2 K Glazing The windows shouldn t be taller than 2,7 m. If the windows are taller, than the floor temperature of the zone directly along the facade should be increased to a maximum of 35 C; The glazing surface should be have a maximum of 50% of the facade surface; Sunscreens (outside) should be applied on the facades with sun load, so the orientations: west, southwest, south and southeast

28 Infiltration The building should have a high air tightness to avoid the risk of draught. This means attention is needed for: the air tightness of the construction between the window frames and the facade; the air tightness of operable windows. 2.2 Flexibility of a building Flexibility is one of the objectives of the whole building design [WBDG, 2009]. Nowadays, there is an increasing need for flexibility, because organization structures change continuously to follow the changes of the economic market and society. As a result the wishes and demands of the user towards the working environment change more frequently and these changes should be accommodated by the building. A building with flexibility has a design that allows changes at several levels to make it possible to adapt to the changing needs of the building owner and user during the complete life time of the building [IFD, 2009]. Flexibility also concerns the flexibility of the building services in order to realize changes in the working environment without loss of thermal comfort. In order to design an installation that can adapt itself to flexibility changes it should be known which parameters are influenced by flexibility and how these parameters are related to thermal comfort. This paragraph describes the flexibility parameters and their relation with thermal comfort Methods of flexibility Businesses and organizations can accomplish different forms of flexibility in relation to their accommodation, namely: Financial flexibility The choice for a certain form of financing (renting, leasing, e.g.) offers the possibility to remove at the moment the organization doesn t fit within the building. Organizational flexibility The organization adapts to the building. This option limits the flexibility, because not all wishes and demands can be realized. Technical flexibility The building can adapt to the wishes and demands that belong to the desired organization structure. In relation to the objective, this thesis considers technical flexibility and leaves financial and organizational flexibility out of consideration. Buildings with technical flexibility are longer suitable for the building owner, because they can be adapted to the current and future needs of the user. This adaptability has a large advantage with regard to sustainability, because fewer materials are needed to change the building and it lengthens the lifetime of the building which prevents early demolition and a reduction of the waste deposit. Technical flexibility isn t limited to constructional changes, but contains also the dilatation and distribution of thermal energy, water, data, electricity supply and building occupants. To achieve technical flexibility different strategies can be applied [IFD, 2009]: Layout flexibility The floor plans can be divided into different layouts, because construction and installation parts can be moved, replaced, adapted, removed or installed

29 Functional flexibility Spaces or the complete building can get another function. This means that both layout and installations can be changed in such way that the space or building can be adapted to the new function. Partitioning The building can be partitioned in several compartments, where every compartment has its own entrance, vertical transport (stairs, elevators) and sanitary facilities. Over dimensioning An over dimensioned building design has a larger floor surface than necessary. The extra floor surface can be used at the moment it is required. This is a form of physical over dimensioning. Non-physical over dimensioning is also possible by taken into account future expansion in horizontal (extra terrain) or vertical (extra floors) way. With regard to the required installation components flexibility by means of partitioning or over dimensioning means that the power of the central components should be over dimensioned and that the infrastructure should be separated for each compartment. However, this kind of flexibility doesn t has a direct influence on the flexibility of the installation components at space level, e.g. Concrete Core Conditioning. Therefore, the flexibility strategies partitioning and over dimensioning are outside the scope of this thesis Flexibility related to utilization and building parameters With technical flexibility a building can undergo several changes during its lifetime. These changes can affect several parameters that are related to the properties of a specific zone or even the complete building. An overview of the parameters that can be changed by layout and function flexibility is given in table 2.4. Strategy Influenced parameters by flexibility strategy Layout flexibility the zone s geometry the zone s orientation (including vertical or horizontal) Function flexibility the zone s function the number of functions within a building Table 2.4: Parameters that can be changed by technical flexibility Flexibility changes (table 2.4) have an indirect relationship with the parameters that influence the thermal comfort in a zone. An example of this relationship is the change of a zone s function that can result in increasing internal heat gains or the change of a zone s geometry which can result in a larger facade surface and, therefore, increasing external heat gains. The parameters that influence the thermal comfort in a zone and linked to flexibility changes are categorized in utilization and building properties. An overview of these parameters is given in table 2.5. The parameters presented in this table are in this thesis used as representation of flexibility

30 Utilization properties Building properties Internal heat gains External heat gains Construction properties Orientation persons lighting equipment facade insulation glass properties surface insulation g-value air infiltration geometry construction mass thermal properties facade orientation location in building horizontal vertical Table 2.5: Overview of flexibility parameters: parameters that influence the thermal comfort in a zone and linked to technical flexibility. These parameters are categorized in utilization and building properties. 2.3 The indoor environment The indoor environment affects the well being of the building occupants. The quality of the indoor environment is determined on basis of several aspects, namely: air quality, thermal, visual and acoustic comfort. A relatively good indoor climate improves the health and comfort of the building occupants and with that the productivity and absence because of illness [Boerstra, 2006]. The productivity of employees can even increase up to 10 to 15% if the building has a relatively good indoor environment [Boerstra, 2003]. One of the aspects that contributes significantly to the quality of the indoor environment (in relation to productivity) is the indoor temperature. Research proves that an indoor temperature above neutral (24 25 C) results in a productivity decrease of 3 to 7% per C. The objective of this thesis considers the behaviour of Concrete Core Conditioning in relation to the achievable indoor thermal comfort. Therefore, only thermal comfort is taken into account to evaluate the indoor environment Thermal comfort The perception of thermal comfort is related to the thermal heat balance of the body. The comfort theory of Fanger is used to calculate a prediction of the thermal comfort and describes a relationship on basis of the individual parameters: physical activity and clothing and the environmental parameters: air temperature, mean radiant temperature, air velocity and relative humidity. This relationship relies on research among a large group of people. Therefore, the calculation results in the PMV (Predicted Mean Vote) and stands for the expected mean appreciation of the thermal comfort and expressed by a scale from -3 to +3 (figure 2.8)

31 PMV Perception Hot Warm Slightly warm Neutral Slightly cool Cool Cold Calculating an average value means that there always be individuals that don t agree with the Predicted Mean Vote. Because it s useful to predict the number of people that feel dissatisfied with the indoor climate the PPD (Predicted Percentage Dissatisfied) has been introduced. The PPD has a direct relationship with the PMV (figure 2.9) and calculates the percentage of people that likely feel uncomfortable with the indoor climate, because it s too cold or too hot. The PMV expresses the perception of the thermal comfort for the body as a whole and, therefore, known as general thermal comfort. However, it s also possible to experience local thermal discomfort by unwanted cooling or heating of one particular part of the body, like draught or vertical temperature differences. Criteria to realize a good indoor thermal climate are specified in standards. These standards distinguish several comfort categories which can be applied on basis of the desired thermal comfort. An overview of the criteria for general and local thermal comfort is enclosed in annex A. Evaluation methods The thermal comfort conditions in a building over time can be evaluated on basis of several methods. One of the methods is to evaluate the general thermal comfort by calculating the percentage of occupied hours the operative temperature is outside a specified range [ISO 7730, 2005]. In this case the operative temperature is used as an equivalent of the PMV, because the operative temperature can be verified in practice and, as even important, can be communicated straightforwardly with people that have no knowledge about the evaluation of thermal comfort. An overview of evaluation methods, based on standards and literature, is enclosed in annex B The operative temperature as performance indicator Predicted percentage Dissatisfied [%] ,5-2 -1,5-1 -0,5 0 0,5 1 1,5 2 2,5 3 Predicted Mean Vote Figure 2.8: PMV scale [0] Figure 2.9: PPD as function of the PMV [0] The operative temperature, which is the mean value of the air and radiant temperature, isn t standardized. This means that the standardized PMV values should be converted to equivalent operative temperatures to evaluate the thermal comfort. The equivalent values can be calculated by using the PMV equations that have the following parameters [ISO 7730, 2005]: Metabolic rate [met]; Clothing insulation [clo]; Air temperature [T]; Mean radiant temperature [T mrt ];

32 Relative air velocity [m/ s]; Relative humidity [%]; An overview of the standardized PMV categories and an example of the equivalent operative temperatures ranges is given in table 2.6. Comfort category PMV Operative temperature Summer Winter [ - ] [ C] [ C] A -0,2 < PMV < +0,2 24,5 1,0 22,0 1,0 B -0,5 < PMV < +0,5 24,5 1,5 22,0 2,0 C -0,7 < PMV < +0,7 24,5 2,5 22,0 3,0 Table 2.6: PMV values and equivalent operative temperatures that apply for each of the comfort categories [ISO 7730, 2005]. The operative temperatures are based on a metabolic rate of 1,2 met, clothing insulation 0f 0,5 clo in summer and 1,0 clo in winter, a turbulence intensity of 40%, an air temperature equal to the operative temperature and a relative humidity of 60% in summer and 40% in winter. As mentioned in the caption of table 2.6 the operative temperature ranges count under certain assumed conditions. These assumptions include a definition of the clothing insulation for winter (1,0 clo) and summer (0,5 clo), but lack a definition of the winter and summer period. However, the evaluation of the thermal comfort for a whole year requires insight in people s clothing behaviour throughout a year to calculate the year-round equivalent operative temperature ranges. Research of De Carli et al. [De Carli, 2007] presents the analysis of people s clothing behaviour that brought a relationship between the external temperature and people s clothing insulation (figure 2.10). This relationship, which is used for the mean clo value, results in a lower maximum and a slightly lower minimum value for the clothing insulation in relation to the design conditions of the ISO 7730 [ISO 7730, 2005] (figure 2.11). Clothing insulation [clo] 1,1 1,0 0,9 0,8 0,7 0,6 0,5 0,4 0, Outdoor temperature [ C] Mean clo [De Carli et al] Winter condition [ISO 7730] Summer condition [ISO 7730] Figure 2.11: Clo-value vs. mean daily outdoor temperature [De Carli, 2007] Figure 2.10: Design clo-values of ISO 7730 vs. mean clo relationship of De Carli et al. The relationship found by De Carli et al. for the clothing behaviour can be used as basis for the calculation of the equivalent operative temperature ranges that can be applied throughout the year. As the clothing behaviour depends on the outside temperature, the calculations will result in operative temperature ranges that are a function of the outside temperature. These calculations have been performed and the resulting temperature ranges are presented in table 2.7 and visualized in figure An overview of the calculation method and assumptions is enclosed in annex C

33 Comfort category PMV Year-round operative temperature Minimum Maximum [ - ] [ C] [ C] A -0,2 < PMV < +0,2 22,2 + 0,054 T e 23,9 + 0,043 T e B -0,5 < PMV < +0,5 21,6 + 0,063 T e 25,5 + 0,035 T e C -0,7 < PMV < +0,7 21,2 + 0,068 T e 26,5 + 0,030 T e Table 2.7: Equivalent operative temperature ranges as function of the outside temperature for each of the comfort categories A, B and C. The operative temperatures are based on a metabolic rate of 1,2 met. See annex C for all assumptions. Looking at the allowable minimum and maximum values of the operative temperatures relatively large differences can be seen (figure 2.13) between the example design conditions of the ISO 7730 [ISO 7730, 2005] and the temperature ranges based on the clothing behaviour relationship of De Carli et al. These differences can be ascribed to: Differences between the assumed conditions for clothing insulation as can be seen in figure 2.11; Differences between the assumptions for the relative air velocity. For the calculations based on De Carli s et al. relationship the mean air velocity according to table A.5 of the ISO 7730 [ISO 7730, 2005] has been used. Operative temperature [ o C] Outside temperature [ o C] Cat. A - min Cat. A - max Cat. B - min Cat. B - max Cat. C - min Cat. C - max Figure 2.12: Operative temperature ranges as function of the outside temperature. The ranges are equivalents of the PMV categories A, B and C [ISO 7730, 2005] and based on De Carli s et al. relationship for the behaviour of clothing insulation [De Carli, 2007]

34 28 27 Operative temperature [ o C] Outside temperature [ o C] Cat. A ISO 7730 Cat. B ISO 7730 Cat. C ISO 7730 Cat. A De Carli Cat. B De Carl Cat. C De Carl Figure 2.13: Operative temperature ranges based on De Carli s et al. relationship in comparison with the example design criteria of ISO Summarizing the evaluation by means of the operative temperatures requires the calculation of the equivalent temperatures of the standardized PMV values. Examples of these equivalent temperatures are described in the international standard ISO 7730 [ISO 7730, 2005], but only for the summer and winter period. However, the found relationship of De Carli et al [De Carli, 2007] makes it possible to calculate the equivalent operative temperatures that can be applied throughout the year. These equivalent operative temperature ranges are presented in figure Sensitivity and uncertainty analysis Buildings and its systems are a complex system of physical processes that have a dynamic interaction. Based on physic principles these interactive processes can be modelled mathematically to result in a building simulation model. This model can be used to make simulations in order to predict the behaviour of a building and its systems. Engineers use building simulation models to support their decision making in the design process. To make the appropriate decisions that result in the desired performance of the building and its systems it is necessary to have insight in the sensitivity and uncertainty of the simulation outputs. Uncertainty and sensitivity analysis are used to assess the sensitivity and uncertainty of a building simulation model s output by means of quantification that is necessary to make an effective use of building simulation [Macdonald, 2002] Uncertainty versus sensitivity In the assessment of a model s output sensitivity and uncertainty are related, but there are some differences. Sensitivity analyses are performed to assess the sensitivity of the simulation output for every single input parameter. The results give insight in the input parameters that have the strongest impact on the simulation output and, therefore, should be chosen well considered. For sensitivity analysis insight in the likely variation of the input parameters is unnecessary [Macdonald, 2002]. For uncertainty analysis, however, this insight is critical, because the objective is to assess the total variation of the simulation output caused by the possible variation of all input parameters

35 2.4.2 Sources for uncertainty A simulation model is subjected to many sources of uncertainty. With uncertainty analysis the sources of uncertainty can be addressed to a specific category. An overview of these categories is presented in table 2.8. Category of uncertainty specification modelling numerical scenario Caused by incomplete specification of the system to be modelled introduction of assumptions and simplification of complex physical processes discretization in time external conditions imposed on the building, e.g. outdoor climate and occupant behaviour Table 2.8: Categories of uncertainty sources, including their causes [Wit, 2006] Techniques for sensitivity and uncertainty analysis The available techniques to quantify the sensitivity and uncertainty of the output of building simulation models are divided into two different approaches, namely internal and external methods [Macdonald, 2002]. The essential difference between these approaches is based on the location where the alterations are made: inside or outside the model. External methods analyse the relationship between the variation of the output and changes in the input parameters. This approach treats the simulation model as a black box that is used to make simulations repeatedly with different sets of input parameters. Internal methods, however, quantify the total uncertainty of a model by altering the mathematic relationships of the simulation model. This results in the advantage just a single simulation has to be performed to calculate the total effect of uncertainties, while the effects are known at all stages of the simulation process. Uncertainty and sensitivity analysis by means of internal methods is outside the scope of this thesis. Therefore, only sensitivity and uncertainty analysis techniques that belong to the external methods approach are considered. Analysis techniques that belong to the external methods approach are divided into local and global methods [Lomas, 1992; Macdonald, 2002]. Local methods describe the influence on the output with regard to changes in individual input parameters, whereas global methods quantify the overall uncertainty with regard to changes in all input parameters. Each of these methods has their specific use [Lomas, 1992]: Local methods With local methods the input parameters are identified to which the output of the model is sensitive or insensitive. This knowledge makes it possible to distinguish the input parameters that should be chosen well considered during the design process in order to improve it. Furthermore, local methods give insight in the parameters tare critical to the output and, therefore, should only be chosen by very skilled building simulation users. Global methods The overall uncertainty gives insight in the accuracy of a model s output and is used to check if the assumptions within the model are sufficiently accurate. Furthermore, the output s accuracy is necessary if the model s predictions are used to compare with measured data or to have insight in the chance that a design parameter exceeds a desired design condition

36 Differential Sensitivity Analysis (DSA) is the best known local method. The analysis starts with a simulation with the input parameters on their most likely base case value. Successively, simulations are performed repeatedly with just one input parameter variation at a time, while the other input parameters stay on their fixed base case values. This makes the interpretation of the results easy, because the changes in output are a direct result of the changes made to just a single input parameter. The disadvantage is that the combined effect of the variations of each of the parameters can only be calculated if the superposition principle is valid for the system, i.e. the system is linear and the effect of each individual input on the output is independent of other input parameters. However, this is not always the case in building physics [Lomas, 1992; Macdonald, 2002]. The factorial method is sometimes used to overcome the disadvantages of DSA, because it includes the interactions between the different input parameters. It is performed by making simulations for all possible combinations of the input parameter values. However, this method is only suitable for small amounts of uncertain parameters, while the required number of simulations grows factorially with the number of uncertain parameters. Methods that are derived from the DSA and factorial method are Cotter s method and the method of Morris. Nevertheless, these methods are more appropriate for the identification of critical parameters instead of the quantification of the uncertainty of the output [Macdonald, 2002]. All global methods are part of the Monte Carlo Analysis (MCA). An MCA starts with the definition of the probability distribution of each the input parameters. Subsequently, a large amount of simulations is performed, typically 80 [Macdonald, 2002], with a random selected set of input values. For the random selection different sampling techniques can be used that ensure the full range of the probability distribution is used. The output results are analysed with the use of statistical methods. Monte Carlo Analysis can be applied even if the superposition principle doesn t count for the system. The analysis takes into account the interaction between the input parameter and their collective effect on the output. However, this method is not suitable to quantify the effect an individual parameter variation has on the output

37 3 MODELLING The heat flow in a building is a result of a complex interaction of processes that take place within the building. These processes can be simulated with the use of a building simulation model. In order to gain insight in the behaviour of Concrete Core Conditioning a building simulation model has been developed that can simulate the heat flow in a building that is applied with Concrete Core Conditioning. The system considered and been modelled into a dynamic simulation model is presented in figure 3.1. This figure shows that this complete system can be divided into 3 separate interacting systems: a multi zone building, Concrete Core Conditioning and a mechanical ventilation system (HVAC). Therefore, the building simulation model is also divided into 3 separate systems that interact with each other. This is schematically presented in figure 3.2. T w_in T air_supply T e T w_out Φ ccc_water Heating/ cooling CCC water HVAC V air_suppply T air_i T cs T mrt_i Φ ccc_ceiling V infiltration Φ lighting Φ persons Φ equipment Φ ccc_floor q solar_i Building zone applied with Concete Core Conditioning Figure 3.1: Schematic view of the system that has been modelled into a dynamic simulation model. The system consists of a building zone with its internal and external gains, Concrete Core Conditioning applied in the floor and ceiling construction and an HVAC-system to supply ventilation air to the building zone. This chapter describes the background and functions of the developed building simulation model and starts with the theoretical background of each of the systems of the building simulation model. Successively, the second paragraph describes how these systems were connected to result in a CCC building simulation model and how this complete model can be used for performing simulations

38 Multi-zone building Input System Output Concrete Core Conditioning HVAC System System Building simulation model Figure 3.2: Schematic principle of building simulation model with Concrete Core Conditioning All models described in this chapter are included on the CD-ROM that is part of this report. 3.1 Modelling the systems The building simulation model consists of three systems that are connected with each other as presented in figure 3.2. The theoretical background of each of these systems is described in the next paragraphs Multi-zone building system HamBase [Wit, 2006; TUe, 2009] is used for the modelling of the building system and is a model that functions in the software environment of Matlab [Matlab, 2006] & Simulink [Simulink, 2006]. Hambase is a validated model for the heat and vapour flows in a building and is used to simulate the indoor temperatures, the relative humidity and the energy use for heating and cooling for one or more zones. However, for this thesis only the heat flow in the building is taken into account. Within HamBase a building is modelled with the definition of the layout, construction properties, infiltration rate and internal heat gain profiles for every zone separately. As presented in figure 3.3 the input of the model consists of heat and vapour flows. These flows, e.g. the heat flow of a heating and cooling system, can be supplied to every zone of the building separately. The output of the model gives insight in the indoor temperatures, relative humidity and the outside conditions as result of the performed simulation. 1. Indoor air temperature [ C] 1. Heat flow [W] 2. Vapour flow [kg/ s] Input HamBase System 2. Operative temperature [ C] 3. Indoor relative humidity [ - ] 4. Outdoor temperature [ C] 5. Outdoor relative humidity [ - ] Output Figure 3.3: Schematic principle of multi-zone building system HamBase [Wit, 2006; TUe, 2009]

39 Modifications to Hambase To realize the building simulation model the inputs and outputs of each of the systems are connected to each other. HamBase was modified to make the connection between HamBase and the systems Concrete Core Conditioning and HVAC possible. The following modifications were made to the input and output of HamBase: Changes to the input Hambase treats radiant and convective heat differently and, therefore, HamBase requires the definition of a convection factor: a factor that divides the input heat flow into a radiant and convective part. However, just 1 convection factor can be defined for each zone separately. As HamBase is connected to 2 different systems for heating and cooling, Concrete Core Conditioning and HVAC, it is needed to define a convection factor for 2 different heating and cooling systems. Therefore, the input is expanded with an extra heat flow input, including its own convection factor. Changes to the output For the connection between the output of HamBase and the input of the other systems the following changes were made to the output: The operative temperature was replaced by the mean wall temperature. The operative temperature is calculated in the Concrete Core Conditioning model to make it possible to take the surface temperature of the floor and ceiling into account; The following outputs were added: The total wall surface Used to calculate the mean radiant temperature in the system Concrete Core Conditioning; The solar energy that is released in the zone. This solar energy includes the effect of the dimensions and properties of the window; The solar radiation on a horizontal outdoor surface. This radiation is used to simulate the heat balance of a roof applied with Concrete Core Conditioning. The changes made to HamBase resulted in the in- and output structure as presented in figure 3.4. The italic styled items are the modifications to the in- and output of the model and show two separate heat flows as input and an increased amount of outputs according to the preceding description. A complete description of all modifications made to HamBase, a visualisation of the modified Hambase system in Simulink and its parameters is enclosed in annex D. The Matlab code of the modified Hambase files is enclosed in annex L. 1. Heat flow - I [W] 2. Heat flow - II [W] 3. Vapour flow [kg/ s] Input HamBase System 1. Indoor air temperature [ C] 2. Mean wall temperature [ C] 3. Indoor relative humidity [ - ] 4. Outdoor temperature [ C] 5. Outdoor relative humidity [ - ] 6. Wall surface [m²] 7. Solar heat released in zone [W] 8. Solar radiation on outdoor [W/ m²] hor. surface Output Figure 3.4: In- and output structure of the modified HamBase system

40 3.1.2 The Concrete Core Conditioning system A building construction applied with Concrete Core Conditioning exchanges both heat and cold with the surrounding zones. This heat exchange is the result of several heat transfer processes that take place within the construction and between the construction and the surrounding zones. Modelling Concrete Core Conditioning means the incorporation of all these heat transfer processes into a thermal simulation model. This paragraph starts with the description of the mathematic model of Concrete Core Conditioning in an intermediate floor. Successively, the changes are described that are required for this mathematic model to result in the Concrete Core Conditioning simulation model that is suitable for all types of constructions, namely: intermediate floor, ground floor and roof. The paragraph ends with the description of the verification of this simulation model. This paragraph describes the principle used to model the Concrete Core Conditioning system. A complete description of this modelling is inserted in annex E and the accompanying Matlab code is inserted in annex M. Mathematic model of Concrete Core Conditioning for an intermediate floor Heat transfer processes occur between different temperature levels. For a Concrete Core Conditioning System these temperature levels are presented with temperature nodes in figure 3.5. The heat transfer processes that occur within this system are divided into 3 groups: Conduction : between the embedded piping system and the construction and between the several construction layers; Convection : between the construction and the surrounding air; Radiation : between the construction and the surrounding building construction. The heat transfer process of the Concrete Core Conditioning system can be represented with a thermal network. This network consists of thermal resistances (R) for the representation of conduction, convection and radiation and the use capacitors (C) for the representation of the thermal heat storage. Based on figure 3.5 a Resistance-Capacitor network (RC-network) for the Concrete Core Conditioning system is presented in figure

41 q solar_i1 Room 1 T air_i1 T mrt_i1 Layer 1 T cs1 Dc1 T c12 δ Dc21 Layer 2 T c2 Dc2 T w_in d x T w_out Dc23 T c23 Layer 3 T c34 Dc3 Layer 4 Room 2 T air_i1 T cs4 T mrt_i1 Dc4 q solar_i2 Figure 3.5: Schematic view of Concrete Core Conditioning in an intermediate floor q solar_i1 R 21 T c12 R 1 T cs1 R rad_fl_i1 T mrt_i1 T w_in R cv_fl_i1 T air_i1 T w_out R x T c2 C 12 C 1 q solar_i2 C w C 2 R 23 T c23 R 3 T c34 R 4 T cs4 R rad_fl_i1 T mrt_i2 R cv_fl_i1 T air_i2 C 23 C 34 C 4 Figure 3.6: Resistance-Capacitor network (RC-network) of Concrete Core Conditioning system

42 C thermal capacitance [J/ K] δ outside pipe diameter [m] d x pipe spacing [m] D c layer thickness [m] D c21 thickness of upper part of [m] construction layer D c23 thickness of lower part of [m] construction layer q solar_i solar energy released [W/ m 2 ] in zone R thermal resistance of construction [K/ W] layer [K/ W] R x thermal resistance between pipe [K/ W] and centre construction layer R rad radiant heat transfer resistance [K/ W] R cv convective heat transfer resistance [K/ W] T air_i indoor air temperature [ C] T mrt_i indoor mean radiant [ C] temperature T c construction temperature [ C] T cs surface temperature of [ C] construction T w_in water inlet temperature [ C] T w_out water outlet temperature [ C] Indices ce ceiling side of construction fl floor side of construction 1 2 room nr. or construction layer 3 4 construction layer Figure 3.7: Nomenclature for figure 3.4 & 3.5. The figures 3.5 and 3.6 represent a 2-dimensional network of the heat transfer processes within the Concrete Core Conditioning system. An important parameter of this 2-dimensional network is the thermal resistance R x. This resistance allows, under certain restrictions, to represent the 3-dimensional heat transfer between the embedded piping system and the construction into a 1 dimensional heat transfer process. The following mathematical relationship is used for the resistance R x [Koschenz, 2000]: 2 = d c δ a n [6] where: o : outside pipe diameter [m] u 2 : pipe spacing [m] t s : thermal conductivity of construction [W/ m K] A : surface area of construction [m 2 ] D c21/23 : thickness of lower/ upper part of construction [m] The RC-network is used to make a mathematical model of the Concrete Core Conditioning system that consists of a set of Ordinary Differential Equations (ODE). Based on figure 3.5 the following ODE s are formulated for temperature node T 1 and T 4 : i f = f f / f f >3 > f f > < [7] i f = f f / f f >3 > f f > < [8] where: i : thermal capacitance [J/ K] : thermal resistance [K/ W] : convective heat transfer resistance [K/ W] : radiant heat transfer resistance [K/ W] : time [s] : temperature [ C] with the indices : construction layer

43 : construction surface : indoor condition : number of room or construction layer 4 : number of construction layer The complete set of ODE s of the Concrete Core Conditioning system is inserted in annex E. The thermal capacitance (C) and resistance (R) are parameters with constant values that are based on the properties of each of the construction layers. The values of these parameters are calculated with the following relationships: Thermal resistance for conduction: = [9] Thermal capacitance i = [10] where: : specific heat [J/ kg K] : thickness of construction layer [m 2 ] t : thermal conductivity of construction [W/ m K] : density [kg/ m 3 ] : volume of construction layer [m 3 ] In comparison with the thermal resistances (R) of the construction layers the radiant and convective heat transfer resistances (R rad and R cv ) aren t fixed values, because it was chosen to calculate the convective and radiant Heat Transfer Coefficients (HTC) on basis of the surrounding conditions (see 2.1). The following relationships are used to calculate the convective and radiant het transfer resistances: Thermal resistance for convection = > Thermal resistance for radiation = < where: h : indoor convective heat transfer coefficient [W/ m 2 K] h : indoor radiant heat transfer coefficient [W/ m 2 K] A complete description of the parameters C and R is inserted in annex E. Mathematic model of Concrete Core Conditioning for a roof or ground floor Concrete Core Conditioning is not only applied in intermediate floors, but can also be applied in ground floors or roofs. Applying Concrete Core Conditioning in a ground floor or roof means that other surroundings have to be taken into account in comparison with an intermediate floor and these have to be incorporated in the simulation model too. In comparison with an intermediate floor the following surroundings have to be taken into account: [11] [12]

44 In case of a roof construction it has to be taken into account that the top construction surface is surrounded by outdoor conditions, namely the outdoor temperature and solar radiation (figure 3.7). In case of a ground floor it has to be taken into account that the lower construction surface is surrounded by the ground (figure 3.8). T e q solar_e Room - inside Outside T cs1 Ground/ Basement T cs4 Room - inside Figure 3.7: Surroundings for CCC in case of a roof construction. In comparison with an intermediate floor the top surface is surrounded by outdoor conditions: the temperature and solar radiation. 3.9 T e_ground Figure 3.8: Surroundings for CCC in case of a ground floor. In comparison with an intermediate floor the lower surface is surrounded by the ground. 3.8 The introduction of 2 extra possible surroundings implies the RC-network have to be changed too. These changes result, depending on the construction type, in a total of 3 different RC-networks that can represent the Concrete Core Conditioning system. These networks are presented in figure 3.9 and show which part of the RC-network should be changed if there will be chosen for a ground floor or roof instead of an intermediate floor. The introduction of an RC-network for every type of construction means that every type of construction will also have its own set of Ordinary Differential Equations. Based on figure 3.8 it can be concluded that the differences between these sets are restricted to the changes of the ODE s of temperature nodes T 1 and T 4. In comparison with the set of DE s for an intermediate floor the following changes are required if CCC is applied in a ground floor or roof: In case of a ground floor i f = f f / f f > > [13] In case of a roof i f = f f / f > f [14] The complete set of Ordinary Differential Equations that applies for each of the floor types, including the complete description of the parameters C and R, is inserted in annex E

45 q solar_e T c1 R e T e C 1 q solar_i1 Replacement in case of roof R 21 T c12 R 1 T c1 R rad_fl_i1 T mrt_i1 T w_in R cv_fl_i1 T air_i1 T w_out R x T c2 C 12 C 1 q solar_i2 C w C 2 R 23 T c23 R 3 T c34 R 4 T c4 R rad_fl_i2 T mrt_i2 R cv_fl_i2 T air_i2 C 23 C 34 C 4 Replacement in case of ground floor T c4 R e T e_ground C 4 Figure 3.10: RC-network of Concrete Core Conditioning system: 3 possible structures. In comparison with the RCnetwork of an intermediate floor (figure 3.5) the part from temperature node T 1 has to be replaced. In case of a ground floor the part from temperature node T 4 has to be replaced. Dynamic simulation model of the Concrete Core Conditioning system The first step in the realisation of the dynamic simulation model was the insertion of the mathematic model in Matlab with the use of an S-function. This S-function contains all sets of Ordinary Differential Equations and relationships to calculate the thermal capacitances (C) and resistances (R) and has the functionality to select the right equations on basis of the selected construction type. Additional calculations were also added to the S-function. The simulation model of the Concrete Core Conditioning system is one of the subsystems of a complete simulation model (figure 3.2). With the use of additional calculations functionalities can be added that are needed for the complete simulation model and an in- and output structure can be realized that fits with the other subsystems. Therefore, the following was decided about the incorporation of additional calculations in the S-function: The addition of the mathematic relationships to calculate the following outputs: The mean radiant temperature; The heating power of floor side of construction; The heating power of ceiling side of construction; The water sided heating power of the CCC construction

46 The equations to calculate these outputs are inserted in annex E. The convective and radiant Heat Transfer Coefficients (HTC) aren t constant values but are calculated on basis of the surrounding conditions (see 2.1.2). However, for practical reasons this calculation isn t incorporated in the S-function, but into a separate system. Therefore, the Heat transfer Coefficients are treated as input. Successively, the S-function was inserted in Simulink where it was connected with its inand output. The structure of the in- and output of the simulation model of the Concrete Core Conditioning system is presented in figure Heat Transfer Coefficients [W/ m 2 K] 5. Solar heat released in zone [W] 6. Solar radiation on horizontal [W/ m²] outdoor surface 7. Indoor air temperature [ C] 8. Mean wall temperature [ C] Outdoor temperatures [ C] Water inlet temperatures [ C] 7. Wall surface [m 2 ] 8. Water mass flow [kg/ s] Input Concrete Core Conditioning System 1. Mean radiant temperature [ C] 2 6. Construction temperatures [ C] 7 9. Surface temperatures [ C] Water outlet temperatures [ C] Heating power [W] 16. Water sided heating power [W] 17. Surface area of floor/ ceiling [m²] Output Figure 3.11: In- and output structure of the Concrete Core Conditioning system A visualisation of the simulation model of the Concrete Core Conditioning system in Simulink and its parameters is enclosed in annex E. Verification of the simulation model After the completion of a simulation model it has to be checked to verify if it functions correctly. This check can be done with a validation, which compares the model s results with measurements, or with a static verification, which compares the model s results with the results of handmade calculations. Because measurements are outside the scope of this project the model was checked with a static verification. The handmade calculations for the verification were performed for every possible construction type (intermediate floor, ground floor or roof) on basis of fixed input values and relationships based on the RC-network of the model (figure 3.10). Successively, simulations were performed with the same fixed input values and its results compared with the results of the handmade calculations. The results of the verification are inserted in table 3.1. The input values and parameters used for this verification are inserted in annex E. Table 3.1 shows that for every model s output the results of the handmade calculations are in accordance with the simulation results. Therefore, it can be concluded that, on basis of static input, the simulation model of the Concrete Core Conditioning system functions correctly

47 Model s Construction type output Intermediate floor Roof Ground floor handmade calculation simulation results handmade calculation simulation results handmade calculation simulation results T mrt 21,68 21,68 22,78 22,78 21,15 21,15 T cs1_rf ,29 43, T cs1 22,96 22,96 22,96 22,96 20,97 20,97 T c2 23,09 23,09 29,05 29,05 19,77 19,77 T c12 23,02 23,02 36,57 36,57 20,40 20,40 T c23 23,26 23,26 28,26 28,26 15,54 15,54 T c34 23,34 23,34 27,86 27,86 13,42 13,21 T cs4 23,35 23,35 27,46 27,46 23,35 23,35 T cs4_gf ,21 13,21 Φ ccc_ceiling 435,23 435, , ,15 532,01 532,01 Φ ccc_floor 611,97 611,97 411,59 411,59 91,02 91,02 Φ ccc_total 1047, , , ,74 623,03 623,03 Φ ccc_water -72,80-72, , , , ,64 A floor/ceiling 38,88 38,88 38,88 38,88 38,88 38,88 T w_out 23,06 23,06 23,06 23,06 23,06 23,06 T w_out_rf ,24 27, T w_out_gf ,73 20,73 Table 3.1: Results of static verification of simulation model of Concrete Core Conditioning system that is performed for every possible floor type: intermediate floor, roof and ground floor These values aren t an output for the specific construction type Heating, Ventilation and Air Conditioning system The Heating, Ventilation and Air Conditioning (HVAC) system of the building simulation model (figure 3.1) consists of an Air Handling Unit (AHU) that is provided with both heating and cooling. With this AHU the fresh outdoor air can be heated or cooled to the desired supply air temperature before it is supplied to the zones. The simulation model of the HVAC-system incorporates the processes that take place within this HVACsystem with regard to the thermal conditioning of the zones and the energy consumption of the AHU. This paragraph starts with a general description about the HVAC-system of this simulation model and the working of heating and cooling coils applied in Air Handling Units. Successively, the mathematic model of the HVAC-system will be described and the implementation of this model in Simulink. The paragraph ends with the verification of this simulation model. General description of HVAC-system When the HVAC-system is in operation the Air Handling Unit conditions fresh outdoor air by heating or cooling before it is supplied to the zones. The supply air temperature of the AHU is controlled with a strategy based on the outside temperature. Taking into account the processes that take place within the HVAC-system the following heat exchange processes can be distinguished: The heat exchange between the Air Handling Unit and the fresh outdoor to condition the air to the desired supply air temperature; The heat exchange between the supplied ventilation air and the air in the zones

48 An AHU heats or cools the outside air with the use of heating and cooling coils (figure 3.12). In practice these coils are connected to a central heating and cooling plant that supplies central heated water to the heating coil and central cooled water to the cooling coil (figure 3.13). When the outside air flows through the AHU the air flows through the coils in which the heat exchange process takes place between the outdoor air and the heated or cooled water system. These heat exchange processes have the following characteristics: The outdoor air heated by the heating coil undergoes a temperature rise. This temperature rise is not accompanied with a change of the absolute humidity of the air as presented in figure If the outdoor air is cooled by the cooling coil the temperature of the air will decrease. This decrease can be accompanied with or without condensation of the air (figure 3.14). This condensation takes place if the mean surface temperature of the cooling coil is lower than the dew point temperature of the outdoor air. Figure 3.12: Picture of coil that can be used for heating or cooling Figure 3.13: Schematic view of Air Handling Unit and its water supply by central power plant3.14 Figure 3.14: Mollier diagram with heating and cooling processes3.13 Mathematic model of HVAC-system For the mathematic model of the HVAC-system the processes that take place within this system were simplified. These simplifications are: The effectiveness of the heat exchange between the water system and the air flowing through the coil is not taken into account; The water inlet and outlet temperatures of the coils aren t an input or output respectively of the mathematic model. The simplifications imply that the mathematic model of the HVAC-system only calculates the energy needed to heat or cool the outdoor air, without taking into account the effectiveness of the heat exchange process in coils

49 The mathematic model of the heating coil is based on the representation of figure 3.15 that shows all variables that are related to the heating coil. Furthermore, the following starting points were used: The supply air volume ( ) is a fixed volume that isn t affected by the heating process; The supply air temperature (T air_supply ) is not an output of the model, but an input, because it is a result of the outdoor temperature based control strategy of the AHU. T e x e V supply_air Φ ahu_hc T air_supply x ahu_hc_out V supply_air T air_supply = supply air temperature [ C] T e = outdoor air temperature [ C] V = supply air volume [m 3 / h] supply_air x e = absolute humidity of [kg/ kg] outdoor air x ahu_hc_out = absolute humidity of [kg/ kg] supply air after heating coil Φ ahu_hc = heating power of AHU to [W] heat supply air Figure 3.15: Schematic representation of heating coil The representation of the cooling coil is presented in figure For the mathematic model of the cooling coil the same starting points were used as the heating coil. The only difference in the modelling process of the cooling coil was the incorporation of the condensation process that can take place in the cooling coil. T e x e V supply_air T ahu_cc_mean x ahu_cc Φ ahu_cc T air_supply x ahu_cc_out V supply_air T air_supply = supply air temperature [ C] T e = outdoor air temperature [ C] T ahu_cc_mean = mean surface [ C] V supply_air temperature of cooling coil = supply air volume [m 3 / h] x e = absolute humidity of [kg/ kg] outdoor air x ahu_cc_out = absolute humidity of [kg/ kg] supply air after cooling coil x ahu_cc = absolute humidity on [kg/ kg] surface of cooling coil Φ ahu_cc = cooling power of AHU to [W] cool supply air Figure 3.16: Schematic representation of cooling coil Based on the representations of the heating and cooling coil, the characteristics of the heating and cooling process and the described starting points the relationships of the mathematic model of the HVAC system were formulated. These relationships are enclosed in annex F

50 Dynamic simulation model of the HVAC system The dynamic simulation model of the HVAC system was realized by implementing the mathematic model directly into Simulink. This resulted in 1 subsystem of the HVAC system that can be easily connected to the in- ands output of the system. The structure of the in- and output of the simulation model of the HVAC system is presented in figure Outdoor air temperature [ C] 2. Outdoor relative humidity [ - ] 3. Indoor air temperature [ C] HVAC System 1. Heating power of AHU [W] 2. Heating power of supply air [W] 3. Supply air temperature [ C] Output Figure 3.17: In and output structure of the HVAC system A visualisation of the simulation model of the HVAC system in Simulink and its parameters is enclosed in annex F. Verification of the simulation model The simulation model of the HVAC system is, just like the simulation model of the Concrete Core Conditioning system, not validated, but checked with a static verification. This static verification has been performed by calculating the relationships of the mathematic model by hand on basis of fixed input values. These fixed input values were also used for the simulations and its results were compared with the results of the handmade calculations. The verification was performed for both a cooling and heating situation. The results of the verification are presented in table 3.2. The input values and parameters used for this verification are enclosed in annex F. Model s Situation type output Cooling Heating handmade calculation simulation results handmade calculation simulation results Φ ahu_central_total ,0 821,4 821,4 Φ ahu_central_zone (1) ,0 464,3 464,3 Φ ahu_central_zone (2) ,6 357,1 357,1 Φ ahu_central_local_zone (1) ,0 85,1 85,1 Φ ahu_central_local_zone (2) ,2 23,8 23,8 T air_supply 22-22,0 20,3 20,3 Table 3.2: Results of static verification of simulation model of HVAC system that is performed for both a cooling and heating situation. Table 3.2 shows that for every model s output the results of the handmade calculations are in accordance with the simulation results. Therefore, it can be concluded that, on basis of static input, the simulation model of the HVAC system functions correctly

51 3.1.4 System for Heat Transfer Coefficients The heat transfer between a construction surface and a space depends on the size of the temperature difference between the construction and space, but also on the size of the Heat Transfer Coefficient (HTC). This coefficient consists of a convective and radiant part and is related with the surface temperature of the construction. Because, the simulation model of the Concrete Core Conditioning system uses the HTC s as input of its model, another system is required to calculate the HTC s that apply for the constructions. In a complete description is given about Heat Transfer Coefficients and how they can be calculated. Based on this description, this paragraph describes the mathematic model of the system that calculates the Heat Transfer Coefficients that apply for roofs and ceiling of intermediate floors. Successively, the implementation of this model and the verification is described. Mathematic model of HTC system and its implementation in Simulink The mathematic model of the HTC system consists of the relationships that are used to calculate the convective and radiant part of the Heat Transfer Coefficient. These relationships are described in These relationships were directly implemented in Simulink to result in a system that can be connected to its in- and output. The structure of the in- and output of the HTC system is presented in figure Mean radiant temperature [ C] 2. Indoor air temperature [ C] 3. Surface temperature of construction - floor [ C] 4. Surface temperature of construction - ceiling [ C] Input Figure 3.18: In- and output structure of HTC-system HTC System 1. Radiant heat transfer coefficient - floor [W/ m 2 K] 2. Radiant heat transfer coefficient - ceiling [W/ m 2 K] 3. Convective heat transfer coefficient - floor [W/ m 2 K] 4. Convective heat transfer coefficient - ceiling [W/ m 2 K] Output A visualisation of the simulation model of the HTC system in Simulink is enclosed in annex G. Verification of the HTC-system To verify if the relationships are correctly implemented in the Simulink system, the system was checked with a static verification. The results of this verification are presented in table 3.3. The input values used for this verification are enclosed in annex G. On basis of the in table 3.3. it can be concluded that the relationships to calculate the convective and radiant part of the Heat transfer Coefficients are correctly implemented in Simulink

52 Model s output Results handmade calculation simulation h rad_ce_i (zone 1) 5,01 5,01 h rad_ce_i (zone 2) 4,72 4,72 h rad_fl_i (zone 1) 5,01 5,01 h rad_fl_i (zone 2) 4,72 4,72 h cv_ce_i (zone 1) 1,14 1,14 h cv_ce_i (zone 2) 1,17 1,17 h cv_fl_i (zone 1) 0,54 0,54 h cv_fl_i (zone 2) 4,32 4,32 Table 3.3: Results of static verification of simulation model of HTC system

53 3.2 The CCC building simulation model The CCC building simulation model is a combination of several systems. Originally, the connection of 3 systems (figure 3.2) should result in the CCC building simulation model. For practical reasons, however, a fourth system was added for the calculation of the Heat Transfer Coefficients. The connection of the four systems with their in- and outputs resulted in the CCC building simulation model as schematically presented in figure System Multi-zone building Input HTC Output System Concrete Core Conditioning System HVAC Figure 3.19: Schematic principle of the CCC building simulation model. In comparison with figure 3.2 a fourth system for the calculation of the Heat Transfer Coefficients was added. This paragraph describes the CCC building simulation model and starts with a description about the structure of the complete simulation model in Simulink and how it can be used for simulations. Successively, a description is given of the data output of the model. The paragraph ends with a description that explains how series of simulations can be run programmatically The complete model Building simulation model All systems of the building simulation model were made in the software environment of Matlab and Simulink. The connection of the systems was made in Simulink and resulted in the CCC building simulation model as presented in figure Within this figure each of the systems as described in 3.1 can be distinguished. Besides, 2 other parts can be distinguished: Data output This part concerns the tools that are available to save and visualize the simulation results. A complete description is given in the next paragraph ( 3.2.2). Attendance profile This system is added for the visualisation of the simulation results and is used to define the time that the building occupants are inside the zones. To perform a simulation with the CCC building simulation model parameters have to be defined in several files, before the simulation can be started in Simulink. The steps to be done to perform a simulation, including the required simulation files, are described in annex H

54 Multi zone building HVAC Heat Transfer Coefficients Concrete Core Conditioning Attendance profile Data output Figure 3.20: CCC building simulation model in Simulink and the parts of the model that can be distinguished

55 3.2.2 Data output After a simulation has been performed the simulation results become available for analysis. The results can be analyzed with the use of standard graphs that are part of the building simulation model or the results can be exported to txt-files for analysis with other software tools. Plotting the standard graphs or exporting the data can be done automatically by selecting the buttons in the data output part of the Simulink model. A description of the results of each of these buttons is presented in table H.1 of annex H Simulation automation If simulation series have to be performed it can be useful to automate the simulation process. By automating the simulation process multiple simulations can be performed in a row automatically which makes the performance of simulation scenarios easier and more time efficient. Therefore, an automated version of the CCC building simulation model was also made. The automated version of the CCC building simulation model performs the required simulations automatically by following some specific steps. These steps are schematically presented in the flow chart of figure 3.21 and concern: The input of parameter values To control the input values and their alteration the automated model contains an additional m-file that has the following functions: It contains the simulation scenarios; It specifies for every scenario: which input parameter should be changed; for every input parameter the values that should be used as replacement. After a specific scenario has been selected the m-file will replace the input value of the parameter with a value according to the simulation scenario; The replacement of input values is repeated until simulations have been performed for all parameter values of the simulation scenario. Performing the simulation The simulation starts automatically after the input values of the parameters have been replaced with another value according to the simulation scenario. Saving simulation results The results of every simulation are saved to a txt-file. Besides, the Matlab Workspace is saved to a mat-file. Repeating simulation cycle The simulation cycle is repeated until the simulations for all parameter values of the selected scenario are performed. To perform simulations with the CCC building simulation model automatically a step-bystep guide is inserted in annex H

56 Replace input Scenario_parameters.m Perform simulations input type simulink m-file Input_AHU Input_HB.m Input_CCC Input_CCC.m system Air Handling Unit Multi-zone building CCC Save output txt workspace data_output.txt data_output.mat Figure 3.21: Flow chart of automatically run simulation series. The steps within this flow chart have to be repeated until simulations for all parameter values of the simulation scenario have been performed

57 4 METHOD TO EVALUATE BEHAVIOUR CONCRETE CORE CONDITIONING 4.1 Method The building simulation model was developed in order to evaluate the behaviour of Concrete Core Conditioning in relation to the flexibility of a building concept. This chapter describes the method used for this evaluation. The first paragraph of this chapter starts with a description of the method and introduces the case study. The second paragraph describes the case study which was used to convert the flexibility parameters into simulation parameters and scenarios. Successively, a description is given about the used performance indicators to evaluate the simulation results. The chapter ends with a description about the performed sensitivity analysis to evaluate the sensitivity of the simulation results for changes in input parameter values. The evaluation of the behaviour of Concrete Core Conditioning in relation to a flexible building concept was, in accordance with the objective of this thesis, focused on gaining insight in: 1. The influence of utilization and building parameters on the behaviour of CCC; 2. The behaviour of CCC in combination with installation components that are used additionally to control the thermal comfort in a zone. This evaluation has been done by performing multiple simulation scenarios and analyzing the simulation results on basis of three different performance indicators and a sensitivity analysis. The following steps describe the process of this evaluation: 1. Definition of simulation scenarios The simulation scenarios performed with the building simulation model were formulated on basis of a case study. This case study concerns a building with a flexible building concept for which several scenarios were formulated with regard to the function, geometry and orientation of zones. On basis of these scenarios the simulation scenarios were determined. These simulation scenarios contain all input parameters of the simulation model and describe for every input parameter their possible values. 2. Performing the simulation scenarios On basis of the simulation scenarios a reference situation was selected which describes the reference value of each of the input parameters. On basis of this reference situation the simulations for each of the scenarios were performed for 2 different local control strategies of the indoor operative temperature: Self control of the indoor temperature In this situation the temperature in the zone completely depends on the self control ability of the Concrete Core Conditioning system. With this control strategy the simulation results will give insight in the solely use of CCC. Active control of the indoor temperature In this situation an additional installation component maintains a specified indoor temperature range. This control strategy gives insight in the use of CCC in combination with an additional installation component

58 All parameters of the building simulation model that weren t part of the simulation scenario were set as boundary condition. This resulted in a list of boundary conditions that was applied for all simulations. 3. Result analysis a. Performance The behaviour of Concrete Core Conditioning has been evaluated on basis of the following performance indicators: Thermal comfort; Thermal power; Energy consumption. 4.2 Case study b. Sensitivity To distinguish the influential from the less influential input parameters a sensitivity analyses was performed. This analysis evaluates the sensitivity of the simulation results for changes in individual input parameters. The case study is based on the definition of a flexible building concept ( 2.2.2). This definition resulted in the following general formulation of the case study: A multi-zone building applied with Concrete Core Conditioning that can be adapted to accommodate changes of the working environment so that the function, geometry and orientation of the zones within the building can be changed over time. More specifically, this building concerns a multi-storey building with floors that can be adapted freely to every possible lay-out (figure 4.1). To condition the zones the building is applied with Concrete Core Conditioning (CCC) for heating and cooling and an Air Handling Unit (AHU) for the mechanical supply of fresh air (figure 3.1). For both the CCC and the AHU counts that their control strategy is not related with the indoor temperature. Therefore, the climate system can be extended optionally with a local convector to maintain the indoor temperature between specified ranges. Figure 4.1: Schematic representation of the case study s building: a multi-storey building with freely adaptable floors

59 The building properties with regard to the accommodated functions, geometry, construction properties and facade qualities can have several values. An overview of these building properties, including their possible values, is presented in table 4.1. The zone s orientation, location and floor are specifically listed within this table, because the freely adaptable floors make it possible to locate a zone everywhere within the building. Building property Unit Possible value I II III IV A zone s: function - office conference room class room hospital - ward orientation - North East South West location - corner intermediate internal floor - intermediate ground top geometry m 3,6 x 3,6 5,4 x 3,6 5,4 x 7,2 Construction mass roof kg/ m floor/ ceiling kg/ m ground floor kg/ m external wall kg/ m internal wall kg/ m Facade glass surface 1) g-value 2) sunscreens 3) % % yes no 100 Table 4.1: Overview of the case study s variable building properties. The table shows for every building property its possible values, e.g.: the construction mass of the roof can have 3 different values: 150, 325 or 500 kg/ m 2. 1) Glass surface as percentage of the complete facade surface; 2) Values based on solar control glass with g-value of 30% or neutral glass with g-value of 60%; 3) Sun blinds on outside of facade Input parameters A simulation model is specified by the definition of its parameters. The parameters of the CCC building simulation model were, on basis of the flexibility parameters ( 2.2.2), categorized into 4 different categories and classified as: input parameter : a parameter that is related to flexibility and for which its effect on the simulation results will be evaluated. boundary condition : a parameter which has a fixed value that is applied for all simulations. The categorized and classified parameters of the CCC building simulation model are presented in table I.1 of annex I. The input parameters are presented in table 4.2. Building Utilization System - CCC System AHU orientation of facade internal heat gains floor/ ceiling construction supply air volume location of room within building thickness geometry density sun entrance specific heat construction mass thermal conductivity Table 4.2: Input parameters of the building simulation model divided into the categories building, utilization and system parameters

60 Based on the definition of the flexibility parameters, table 4.2 should present the aspects air infiltration, facade and glass insulation as an input parameter. However, it was decided to classify these parameters as boundary conditions, because in practice these parameters remain constant independent of the zone s location within the building. The combination of the values of the variable building properties (table 4.1) and the input parameters of the simulation model (table 4.2) resulted in multiple values for each of the simulation input parameters. These values are presented in table 4.3. The method used to calculate these values is enclosed in annex J. Category Input parameter Unit Possible values I II III IV V VI VII building orientation orientation of facade - North East South West location within building horizontal location within building vertical - corner intermediate internal - ground intermediate top geometry of room small medium large depth width height m m m 3,6 3,6 2,7 5,4 3,6 2,7 5,4 7,2 2,7 sun entrance building & construction mass 1) low medium high system CCC roof floor/ ceiling ground floor external wall internal wall kg/ m 2 kg/ m 2 kg/ m 2 kg/ m 2 kg/ m internal heat gains W/ m system - AHU supply air volume ACH Table 4.3: Overview of input parameter values. The table shows for every input parameter several possible values, e.g.: the construction mass of the building can have 3 different values: low, medium and high. 1) The geometry and properties (density, thermal conductivity and specific heat) of every floor type and each construction mass are inserted in annex I Boundary conditions The boundary conditions are the parameters that have a fixed value during all simulations to be performed. An overview of all used boundary conditions is inserted in annex J. The following boundary conditions are specifically mentioned: Reference year All simulations were performed for a complete year. The selected year concerns the period from 1 May 1974 till 1 May This year is characterized as a year with an average climate, so without extreme hot and cold periods

61 Control strategy for water inlet temperature of Concrete Core Conditioning The water inlet temperature is not related to the indoor temperature and has a fixed value of 23,5 C. This strategy has been chosen on basis of the referenced literature as described in Control strategy for the supply air temperature The simulations are performed to gain insight in the behaviour of Concrete Core Conditioning. Therefore, it was decided to use a control strategy that minimizes the influence of the supply air on the thermal conditioning of the zone. This resulted in a strategy that is not related to the indoor temperature, but only to the outdoor temperature. The relation with the outdoor temperature was made to make it possible to increase the supply air temperature if the outdoor temperature increases too Simulation scenario s A simulation scenario concerns a series of simulations that are performed for multiple values of one specific input parameter. The number of simulations to be performed for a specific scenario depends on the number of values that can be used as replacement for the reference value of the input parameter. The reference situation contains all reference values of the input parameters. These reference values were selected from the possible values as presented in table 4.3 and are visualised in figure 4.2. A sun entrance B construction mass C internal heat gains D supply air volume : 0,18 - : medium : 35 W/ m² : 3,0 ACH A C D 2,7 m B N 3,6 m intermediate floor 5,4 m Figure 4.2: Reference values of input parameters. A total of 8 different input parameters were selected and for each these input parameters multiple possible values were calculated. Therefore, 8 different simulation scenarios were formulated and these are presented in table

62 Scenario Variable input parameter Replacement values Reference value scenario 1 orientation of facade North, East, South West scenario 2 location within building - horizontal corner, internal intermediate scenario 3 location within building - vertical ground, top intermediate scenario 4 geometry of room small, large medium scenario 5 sun entrance 6, 9, 15, 30, scenario 6 construction mass low, high medium scenario 7 internal heat gains 0, 20, 25, 45, 60, scenario 8 supply air volume 1, 2, 4, 5, 6 3 Table 4.4: Overview of simulation scenarios including the reference value of each input parameter. 4.3 Performance indicators The simulation results have been evaluated with the use of three different performance indicators: thermal comfort, thermal power and energy consumption Thermal comfort The thermal comfort has been evaluated by calculating the percentage of occupied hours that the operative temperature satisfies the ranges as presented in figure 4.3. These ranges define the operative temperature as function of the outdoor temperature for 3 different ranges which are the equivalents of the PMV categories A, B and C of the ISO 7730 [0]. Operative temperature [ o C] Outside temperature [ o C] Cat. A - min Cat. A - max Cat. B - min Cat. B - max Cat. C - min Cat. C - max Figure 4.3: Operative temperature ranges used for the evaluation of the thermal comfort. This graph is also presented in figure 2.12 of Thermal power Within the building simulation model the zones are conditioned with Concrete Core Conditioning and supply air from the Air Handling Unit. To gain insight in the contribution of each of these systems in the thermal conditioning of the zone, the thermal power of both systems was evaluated. The thermal power concerns the power that both systems contribute to the zone locally. This local thermal power was for both systems evaluated during occupied hours on basis of 3 characteristics:

63 Maximum thermal power [W/ m 2 ] Minimum thermal power [W/ m 2 ] Mean thermal power [W/ m 2 ] Energy consumption The total energy consumption is determined by the energy consumption of the Concrete Core Conditioning system and the Air Handling Unit. The energy consumption of both systems was evaluated in order to gain insight in the contribution of each of these systems in the total energy consumption. The energy consumption concerns the total amount of heating and cooling energy used by each of the systems during the time that they are in operation. For each of the systems this energy is used for the following process: Concrete Core Conditioning : heat or cool the water outlet temperature to the required water inlet temperature; Air Handling unit: : heat or cool the outdoor air to the required supply air temperature. 4.4 Sensitivity analysis Several techniques are available to evaluate the sensitivity of a simulation model s output ( 2.4). Taking into account the required number of simulations to perform a sensitivity analysis it was decided to use a local method to evaluate the simulation model s output, namely the Differential Sensitivity Analysis. A Differential Sensitivity Analysis assesses the model s output in relation to changes in individual input parameters. For this analysis the simulation results of each of the performed simulation scenarios were used for the situation the indoor temperature is controlled by the self control ability of Concrete Core Conditioning. Furthermore, it has to be noted that uncertainty is not taken into account which means that the likely variation of the input parameters hasn t been evaluated

64 - 50 -

65 5 SIMULATIONS WITH CONCRETE CORE CONDITIONING The building simulation model was used to perform multiple simulations for each of the simulation scenarios. This chapter describes the results of these simulations that were used to evaluate the behaviour of Concrete Core Conditioning. The first paragraph describes the simulation results of the simulations performed for the scenario that the indoor temperature is controlled by the self control ability of CCC. In the second paragraph the results are presented for the situation the reference situation is applied with an active control strategy of the indoor temperature. The third paragraph describes the sensitivity analysis. Successively, the overall results of the performed simulations are presented. The chapter ends with a discussion about the simulation results. 5.1 Results: self control strategy of indoor temperature This paragraph describes the simulation results of each of the simulation scenarios for the situation that the indoor temperature is not controlled actively, but completely depends on the self control ability of Concrete Core Conditioning. Therefore, the results in this paragraph give insight in the behaviour of the solely use of Concrete Core Conditioning. The simulation results of all scenarios are related to a reference situation. Therefore, the results of the reference situation are described first, before the results of the scenarios are described. An overview of the simulation results of every scenarios is enclosed in table K.1 till K.3 of annex K Reference situation The reference situation that was used for each of the performed simulation scenarios was already presented in figure 4.3 and table 4.4. For the completeness the properties of this reference situation are also presented in figure 5.1. A sun entrance B construction mass C internal heat gains D supply air volume : 0,18 - : medium : 35 W/ m² : 3,0 ACH A C D 2,7 m B N 3,6 m intermediate floor 5,4 m Figure 5.1: Reference situation of all simulation scenarios. This figure is also presented in Furthermore, the same boundary conditions were used for all performed simulations and are presented in table I.3 of annex I. The results of the simulations for the reference situation are presented in figures 5.2 to

66 100 Thermal comfort - reference situation 40 Thermal comfort - reference situation Percentgaes [%] Time of under- and overheating [%] ,5 1, West Category A Category B Category C none -50 Wind direction Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.2: Percentage of time that operative temperature satisfies the categories A, B or C of the ISO Figure 5.3: Percentage of time that minimum and maximum temperature limits of categories A, B or C are exceeded.5.3 The thermal comfort of the reference situation doesn t satisfy the operative temperature ranges of the categories A, B or C during the complete occupation time and this is caused by both over- and underheating (figure 5.3). In this situation the thermal comfort satisfies for 57% of the occupation time the comfort category C, but for 43% of the time this category C can t even be realized (category none ). Exceeding category C is mostly caused by underheating hours, because 43% of the occupation time is the sum of 32% underheating hours and just 11% overheating hours. Concrete Core Conditioning has in this situation an average thermal power of 17 W/ m 2 for heating and 18 W/ m 2 for cooling. The spread between the mean and maximum value of the thermal power for cooling is relatively large (x 5,6) in relation to heating (x 2,0). Furthermore, the supply air contributes with an average heating power of 2,5 W/ m 2 and an average cooling power of 8 W/ m 2 to the thermal conditioning of the zone. For the supply air counts that the relative spread between the mean and maximum cooling power (x 4,7) is almost equal in relation to the difference between the mean and maximum heating power (x 4,1). The total energy consumption for cooling is completely determined by the energy consumption of CCC (98%) and this makes the energy consumption of the AHU (9 kwh) during the whole simulation period negligible. For heating, however, CCC contributes 40% and the AHU 60% to the total energy consumption. Furthermore, the total energy consumption for heating is higher (x 5,6) than the energy consumption for cooling, because the AHU do uses energy for heating. Heating and cooling power [W/ m²] Thermal power CCC - reference situation ,5 1, Wind direction Max. cooling Mean cooling Max. heating Mean heating Heating and cooling power [W/ m²] ,5 1, Thermal power supply air - reference situation Wind direction Max. cooling Mean cooling Max. heating Mean heating Figure 5.4: Local thermal heating and cooling power of Concrete Core Conditioning.5.5 Figure 5.5: Local thermal heating and cooling power of supply air

67 Energy consumption - reference situation Energy consumption [kwh] ,5 1,5 Wind direction CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.6: Energy consumption for heating and cooling of CCC and the total consumption of CCC and AHU Scenario 1: orientation of facade Figure 5.7 and 5.8 present the results for the thermal comfort if the facade orientation of the reference situation changes. These figures present: In the sequence North, East, South the overheating hours increase and the underheating hours decrease. With regard to category C, East and South have an almost equal thermal comfort, but the comfort for orientation North is better (+6,5%); With regard to category C orientation West has an thermal comfort equal to orientation South, but orientation West has more underheating hours and less overheating hours. Percentgaes [%] Thermal comfort - scenario 1 North East South West Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario North East South West Wind direction Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.7: Comparison of thermal comfort for 4 different facade orientations.5.8 Figure 5.8: Comparison of under- and overheating time for 4 different facade orientations

68 The results for the thermal power (figure 5.9 & 5.10) present: The facade orientation has a negligible influence on the heating power of CCC and supply air; The change of the facade orientation has the greatest influence for the cooling power of orientation North: A decrease of the mean power of CCC with 33% to 12 W/ m 2 and a decrease of the maximum power with 56%; The mean power of the supply air also decreases with about 22% to 6 W/ m 2 and the maximum power decreases with 45%. These effects are caused by the reduction of the sun entrance on orientation North. For orientation South the mean thermal power of CCC increases with 15%. 60 Thermal power CCC - scenario 1 40 Thermal power supply air - scenario 1 Heating and cooling power [W/ m²] North East South West Heating and cooling power [W/ m²] North 2 East 3 South 4 West Wind direction -100 Wind direction Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.9: Comparison of thermal power of CCC for 4 different facade orientations.5.10 Figure 5.10: Comparison of thermal power of supply air for 4 different facade orientations.5.9 The energy consumption in relation to the reference situation show (figure 5.11): The facade orientation influences the energy consumption for heating for the orientations North and South. This results in an increase of the total energy consumption for heating of 7% for orientation North and a decrease of 7% for orientation South; Orientation South result in an increase of the energy consumption for cooling of 20% for both CCC and the total energy consumption (while the energy consumption of the AHU remains constant); For orientation North the energy consumption for cooling by CCC decreases with 58%. Energy consumption - scenario 1 Energy consumption [%] 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% -10% -20% % -40% -50% -60% -70% -80% -90% -100% North East South West Wind direction CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.11: Comparison of energy consumption for 4 different facade orientations

69 5.1.3 Scenario 2: location within building horizontal The location of the zone within the building does have an influence on the thermal comfort in the zone (figure 5.12 & 5.13) in relation to the reference situation: If a zone is located along a corner the time that category C is satisfied decreases with 44% and for category A this decrease can even be up to 53%. The decrease of the thermal comfort is slightly higher on the southwest corner, because a southwest (SW) corner has more sun entrance than a northwest (NW) corner which result in more overheating hours on southwest. However, for both corners count that the thermal comfort decreases due to a doubling of the glass surface of the facade; An internal location of the zone result in a large increase of the time that category C is satisfied (+59%), due to a decrease of both over- and underheating hours. However, the time that the category A is satisfied decreases drastically with 72%, because of a great increase of the overheating hours of category A. Percentgaes [%] Thermal comfort - scenario 2 corner, left (SW) corner, right (NW) intermediate internal Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario corner, left corner, right intermediate internal (SW) (NW) 2 floor Location in building Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.12: Comparison of thermal comfort for 4 different zone locations Figure 5.13: Comparison of under- and overheating time for 4 different zone locations The results for the thermal power (figure 5.14 & 5.15) show in relation to the reference situation: Due to the doubled glass surface of the zones along a corner the mean thermal heating power of CCC increases with 60% or 72% to 27 W/ m 2 or 29 W/ m 2 for the northwest and southwest corner respectively. The mean thermal heating power of the supply air increases for both corners with about 180% to 6,5 W/ m 2 ; For the southwest corner the mean cooling power of CCC increases with 68% to 31 W/ m 2 and the mean cooling power for the supply air with 40% to 11 W/ m 2. The spread between the mean and maximum cooling power, for both CCC and supply air, decreases for orientation northwest and increases for orientation southwest. For internal zones the mean heating power of CCC decreases strongly to 4 W/ m 2 (-77%) and its mean cooling power increases slightly to 20,5 W/ m 2 (+12%). For the supply air counts that the mean cooling power remains equal, but the mean heating power decreases to 0 W/ m

70 The energy consumption (figure 5.16) is strongly influenced by the location of the zone within the building. In relation to the reference situation counts: For zones along corners the total energy consumption for heating increases with 36% (SW) to 53% (NW) and automatically result in a larger contribution by CCC in the total energy consumption for heating, because the control strategy of the AHU is fixed; For an internal zone the total energy consumption for heating decreases with 34%; The energy consumption for cooling for the northwest corner and the internal zone remains almost equal, but for the southwest corner the energy consumption for cooling increases drastically with 88%. Heating and cooling power [W/ m²] Thermal power CCC - scenario corner, left 2 3 internal4-30 (SW) corner, right intermediate -50 (NW) floor Heating and cooling power [W/ m²] Thermal power supply air - scenario 2 0 corner, left internal (SW) corner, right intermediate -40 (NW) floor -130 Location in building -100 Location in building Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.14: Comparison of thermal power of CCC for 4 different zone locations Figure 5.15 Comparison of thermal power of supply air for 4 different zone locations Energy consumption [%] Energy consumption - scenario 2 135% 125% 115% 105% 95% 85% 75% 65% 55% 45% 35% 25% 15% 5% -5% -15% -25% % -45% -55% -65% -75% -85% -95% -105% corner, left corner, right intermediate floor internal (SW) (NW) Location in building CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.16: Comparison of energy consumption for 4 different zone locations Scenario 3: location within building vertical In relation to the reference situation (intermediate) the vertical location of the zone within the building has the following effect on the thermal comfort (figure 5.17 & 5.18): The thermal comfort on the ground and top floor is almost equal: On the top floor the time that category C is satisfied increases slightly (+5%), but for the ground floor this increase is negligible (+1%);

71 The over- and underheating hours are almost equal too. Only a small decrease of the over- and underheating hours resulted in the small increase of the thermal comfort on the ground and top floor. Percentgaes [%] Thermal comfort - scenario 3 ground intermediate top Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario ground floor intermediate floor top floor Location in building Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.17: Comparison of thermal comfort for 3 different floors Figure 5.18: Comparison of under- and overheating time for 3 different floors The results for the thermal power (figure 5.19 & 5.20) show: The thermal power of CCC, both heating and cooling, is not influenced by the location of the zone, with exception of the mean cooling power of CCC. On the top floor the mean thermal cooling power increases slightly to 19 W/ m 2 (+3,5%); In relation with the intermediate zone the vertical location of the zone has, in absolute terms, a small influence on the thermal heating and cooling power of the AHU: On both the ground and top floor the mean thermal heating and cooling power decreases; The top floor has the largest decrease and results in a mean heating power of the AHU of 7 W/ m 2 (-10%) and a mean cooling power of 1,9 W/ m 2 (-17%). For both heating and cooling power counts that the spread between the minimum and maximum power remains equal. 60 Thermal power CCC - scenario 3 40 Thermal power supply air - scenario 3 Heating and cooling power [W/ m²] ground floor top floor intermediate -40 floor Heating and cooling power [W/ m²] 20 0 ground floor top floor intermediate floor Location in building -100 Location in building Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.19: Comparison of thermal power of CCC for 3 different floors Figure 5.20: Comparison of thermal power of supply air for 3 different floors

72 In relation to the reference situation the results for the energy consumption (figure 5.21) show: A location on the ground or top floor results in an increase of the energy consumption for both heating and cooling; If the zone is located on the ground floor the total energy consumption for heating increases with 25%. This increase of the energy consumption is caused by the heat loss of the floor construction to the ground, which result in an increase of the energy consumption of CCC with 61% for heating and 43% for cooling; The total energy consumption for heating the top floor increases with 31% and the energy consumption of CCC increased with 76%. This increase is also caused by the heat loss through the roof. Therefore, the energy consumption of CCC for cooling increases with 58%. 80% Energy consumption - scenario 3 70% Energy consumption [kwh] 60% 50% 40% 30% 20% 10% 0% ground floor 1 intermediate floor 2 top floor 3 Location in building CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.21: Comparison of energy consumption for 3 different floors Scenario 4: geometry of room On basis of the results for the thermal comfort (figure 5.22 & 5.23) the influence of the room geometry is limited in relation to the reference situation (medium: 5,4 x 3,6 m): The difference between the medium and large geometry is negligible, because the ratio between the CCC surfaces and the facade surface is equal; The small room geometry result in a decrease of the thermal comfort, because the time that even category C is satisfied decreases with 25% which is caused by an increased under- and overheating time. This is due to an unfavourable ratio between the available CCC surface and the facade surface which has the following consequences: Less available cooling power to meet the equal amount of solar heat that enters the zone; Less available heating power to meet the equal heat loss through the facade. For the thermal power (figure 5.24 & 5.25) also counts that the influence of the room geometry is limited: The thermal power, for both CCC and supply air, increases for the small zone geometry. The increase of the thermal power of CCC is because of its self control ability: Increase of heating power (+25%) if the zone temperature decreases during heating situation (due to relatively higher heat losses); Increase of cooling power (+25%) if the zone temperature increases during cooling situation (due to relatively higher sun entrances)

73 Percentgaes [%] Thermal comfort - scenario 4 small medium large Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario ,6 x 3,6 5,4 x 3,6 5,4 x 7, Geometry Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.22: Comparison of thermal comfort for 3 different zone geometries.5.23 Figure 5.23: Comparison of under- and overheating time for 3 different zone geometries Thermal power CCC - scenario 4 40 Thermal power supply air - scenario 4 Heating and cooling power [W/ m²] ,6 x 3,6 5,4 x 3,6 5,4 x 7, Heating and cooling power [W/ m²] ,6 x 3,6 5,4 x 3,6 5,4 x 7, Geometry -100 Geometry Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.24: Comparison of thermal power of CCC for 3 different zone geometries Figure 5.25: Comparison of thermal power of supply air for 3 different zone geometries The results of the energy consumption (figure 5.26 in kwh/ m 2 ) can be expected: The energy consumption of the large zone is almost equal, because it has the same ratio between the CCC surface and the facade surface; Energy consumption - scenario 4 The total energy consumption of the 50% small zone increased with 17% for 40% both heating and cooling. The energy consumption of CCC for heating even increased with 42%. These increases are caused by the fact that the self 30% 20% 10% control ability of CCC resulted in an increase of the thermal power to 0% % compensate the higher or lower 3,6 x 3,6 indoor temperatures during cooling or 5,4 x 3,6 Geometry 5,4 x 7,2 heating situation respectively. CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Energy consumption [kwh/ m²] Figure 5.26: Comparison of energy consumption for 3 different zone geometries (energy consumption in kwh/ m 2 )

74 5.1.6 Scenario 5: sun entrance The sun entrance is the multiplication of the g-value (%) and the glass surface (%). In relation to the reference situation (sun entrance of 18%) changes in the sun entrance do influence the thermal comfort (figure 5.27 & 5.28): For the chosen boundary conditions a sun entrance of 15% seems an optimum for thermal comfort, because it results in a slightly better thermal comfort (category C: +2%). Furthermore counts for this sun entrance: Lower than 15% result in a decrease of thermal comfort due to underheating; Higher than 15% result in a decrease of thermal comfort due to overheating. The sun entrance has an almost linear relationship with the overheating time. Percentgaes [%] Thermal comfort - scenario Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario Sun entrance [%] Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.27: Comparison of thermal comfort for 6 different sun entrances.5.28 Figure 5.28: Comparison of under- and overheating time for 6 different sun entrances.5.27 On basis of the results for thermal power (figure 5.29 & 5.30) it can be concluded: The thermal power for cooling (CCC and supply air) is most sensitive for changes in the sun entrance, especially the maximum cooling power; The spread between the mean and maximum cooling power increases rapidly with increasing sun entrances, because of the higher solar loads on the CCC constructions; The increase of the mean cooling power is greater than the decrease of the mean heating power. This counts for both CCC and the supply air and in relation to the reference situation can be seen: The mean cooling power of CCC increases up to 80%, while the mean heating power decreases with a maximum of 10%; The mean cooling power of the supply air increases up to 65%, while the mean heating power decreases with a maximum of 54%; The increase of the cooling power is not equal to the decrease of the heating power, because increasing sun entrances result in increasing glass facade surfaces. While the glass facade has less insulation in relation to a closed facade, increasing glass facade surfaces result in increasing heat losses through the facade

75 Heating and cooling power [W/ m²] Thermal power CCC - scenario 5 Thermal power supply air - scenario Sun entrance [%] Heating and cooling power [W/ m²] Sun entrance [%] Max. cooling Mean cooling Max. heating Mean heating Figure 5.29: Comparison of thermal power of CCC for 6 different sun entrances.5.30 Max. cooling Mean cooling Max. heating Mean heating Figure 5.30: Comparison of thermal power of supply air for 6 different sun entrances.5.29 The results of the energy consumption (figure 5.31) fit with the preceding remarks about thermal comfort and thermal power: The energy consumption for cooling increases rapidly and shows a linear relationship with the sun entrance. With a sun entrance of 60% the energy consumption for cooling even increases with 325%; The energy consumption for heating decreases with increasing sun entrances, but this decrease has a maximum of 26% in case of a sun entrance of 60%. Energy consumption [kwh] Energy consumption - scenario 5 400% 350% 300% 250% 200% 150% 100% 50% 0% -50% % Sun entrance [%] CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.31: Comparison of energy consumption for 6 different sun entrances Scenario 6: construction mass The thermal comfort is, in relation to the reference situation (medium), influenced by changes in the construction mass (figure 5.32 & 5.33): If a high construction mass is selected it results in an increase of the time that category C is satisfied (+12%), because of a reduction of over- and underheating hours; The selection of a low construction mass results in a negligible decrease of the thermal comfort (category C: -2%) due to a small increase of the under- and overheating hours. Based on the results of the thermal power (figure 5.34 & 5.35) there can be concluded: The construction mass influences the thermal power of CCC and this is related with the thermal power of the supply air: A high construction mass result in an increase of the thermal power of CCC (+10 cooling/ +4% heating) and a decrease of the thermal power of the supply air (-22% cooling/ -58% heating). The selection of a low thermal mass result in the opposite, but the influence is very small, while the thermal power of CCC for heating decreases with 2% for cooling and 1% for heating

76 Percentgaes [%] Thermal comfort - scenario 6 low medium high Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario low medium high Thermal mass Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.32: Comparison of thermal comfort for 3 different construction masses.5.33 Figure 5.33: Comparison of under- and overheating time for 3 different construction masses Thermal power CCC - scenario 6 40 Thermal power supply air - scenario 6 Heating and cooling power [W/ m²] low medium high Heating and cooling power [W/ m²] low medium high Thermal mass -100 Thermal mass Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.34: Comparison of thermal power of CCC for 3 different construction masses.5.35 Figure 5.35: Comparison of thermal power of supply air for 3 different construction masses.5.34 The energy consumption (figure 5.36) is influenced by the construction mass: A high construction mass has a greater influence on the energy consumption than a low construction mass: A high construction mass result in an increase of the energy consumption with 12% (heating) to 41% (cooling); A low construction mass result in a small increase of the energy consumption: 2% for heating and 9% for cooling. Energy consumption [kwh] Energy consumption - scenario 6 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% low medium high Thermal mass CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.36: Comparison of energy consumption for 3 different construction masses

77 5.1.8 Scenario 7: internal heat gains The results (figure 5.37 & 5.38) show that in relation to the reference situation (35 W/ m 2 ) changes in internal heat gains have a significance influence on the thermal comfort: For the chosen boundary conditions, internal heat gains of 35 W/ m 2 seem an optimum for thermal comfort, because it results relatively in the best thermal comfort. Changes around this optimum result in: Lower than 35 W/ m 2 result in a decrease of thermal comfort due to underheating (up to 49% for category C for 0 W/m 2 ); Higher than 35 W/ m 2 result in a decrease of thermal comfort due to overheating (up to 33% for category C for 75 W/m 2 ). Increasing internal heat gains result in a decrease of underheating and an increase of overheating hours. The underheating hours stabilize around 45 W/ m 2 to 75 W/ m 2 ; Percentgaes [%] Thermal comfort - scenario Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario Internal heat gains [W/ m²] Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.37: Comparison of thermal comfort for 7 different internal heat gains.5.38 Figure 5.38: Comparison of under- and overheating time for 7 different internal heat gains.5.37 On basis of the results for the thermal power (figure 5.39 & 5.40) it can be concluded that changing internal heat gains have a relatively small influence on the heating power, but a great influence on the cooling power: The mean thermal cooling power of CCC doubles if the internal heat gains increase to 75 W/ m 2. However, for internal heat gains from 35 W/ m 2 to 0 W/ m 2 the mean thermal cooling power decreases with just 10% to 16,3 W/ m 2 if the internal heat gains decrease to 0 W/ m 2 ; For the mean thermal cooling power of the supply air also counts that it increases with increasing thermal gains and result in a maximum mean cooling power of 10,5 W/ m 2 (+35%) if the heat gains increase to 75 W/ m 2 ; For both CCC and the supply air counts that the spread between the mean and maximum cooling power increases linear with increasing internal heat gains. This result in the following maximum cooling powers: CCC : 135 W/ m 2 Supply air : 49 W/ m

78 60 Thermal power CCC - scenario 7 40 Thermal power supply air - scenario 7 Heating and cooling power [W/ m²] Heating and cooling power [W/ m²] Internal heat gains [W/ m²] -100 Internal heat gains [W/ m²] Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.39: Comparison of thermal power of CCC for 7 different internal heat gains.5.39 Figure 5.40: Comparison of thermal power of supply air for 7 different internal heat gains.5.40 Based on the results for the energy consumption (figure 5.41) it can be concluded: Changing internal heat gains have a greater influence on the energy consumption for cooling than for heating; The energy consumption for heating doesn t change for internal heat gains between the range of 35 W/ m 2 to 45 W/ m 2 : If the internal gains are lower than this range the energy consumption increases with a maximum of 18% if the internal gains decrease to 0 W/ m 2 ; If the internal gains are higher than this range the energy consumption decreases with a maximum of 14% if the internal gains increase to 75 W/ m 2 ; The energy consumption for cooling isn t affected around internal gains in a range of 35 to 45 W/ m 2. If the internal gains increase the energy consumption almost doubles for internal gains of 75 W/ m 2. For lower internal gains the energy consumption for cooling decreases up to 48% if the internal gains decrease to 0 W/ m 2. Energy consumption [kwh] Energy consumption - scenario 7 110% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% -10% -20% % -40% -50% -60% Cooling CCC Internal heat gains Cooling [W/ m²] CCC+AHU Heating CCC Log. (Cooling CCC+AHU) Heating CCC+AHU Figure 5.41: Comparison of energy consumption for 6 different internal heat gains

79 5.1.9 Scenario 8: supply air volume In relation to the reference situation (3 ACH) the following can be concluded about the results of changing supply air volumes (figure 5.42 & 5.43): With the chosen boundary conditions the thermal comfort decreases slightly if the supply air volume increases from 3 ACH to 6 ACH. This results for a supply air volume of 6 ACH in a decrease of the thermal comfort with 6% (category C); If the supply air volume decreases to 1 ACH the thermal comfort will decrease (5% for category C), because the increase of overheating hours is larger than the decrease of underheating hours. Percentgaes [%] Thermal comfort - scenario Category A Category B Category C none Time of under- and overheating [%] Thermal comfort - scenario Ventilation volume [ACH] Cat. > A Cat. > B Cat. > C Cat. < A Cat. < B Cat. < C Figure 5.42: Comparison of thermal comfort for 6 different supply air volumes.5.43 Figure 5.43: Comparison of under- and overheating time for 6 different supply air volumes.5.42 On basis of the results for thermal power (figure 5.44 & 5.45) can be concluded: The influence of changing supply air volumes on the thermal power of CCC is negligible; The thermal power of the supply air increases linearly with the increase of the supply air volume: The increase of the mean thermal power, both heating and cooling, is not very large (absolute) and result in a mean heating power of 4 W/ m 2 and a mean cooling power of 12 W/ m 2 if the supply air volume increases to 6 ACH; The spread between the mean and maximum power increases rapidly and result in a maximum heating power of 19 W/ m 2 and a maximum cooling power of 56 W/ m Thermal power CCC - scenario 8 40 Thermal power supply air - scenario 8 Heating and cooling power [W/ m²] Heating and cooling power [W/ m²] Ventilation volume [ACH] -100 Ventilation volume [ACH] Max. cooling Mean cooling Max. heating Mean heating Max. cooling Mean cooling Max. heating Mean heating Figure 5.44: Comparison of thermal power of CCC for Figure 5.45: Comparison of thermal power of AHU for 6 6 different supply air volumes.5.45 different supply air volumes.5.44

80 About the relationship between the energy consumption and changing supply air volumes can be concluded (figure 5.46): The total energy consumption for heating has a linear relationship with the supply air volume, because this consumption completely depends on the air volume, while the control strategy of the AHU is fixed; The energy consumption for heating by CCC can be specified in a range of -6% to +6% from the minimum volume of 1 ACH to the maximum supply air volume of 6 ACH; The energy consumption for cooling 70% Energy consumption - scenario 8 60% by CCC is influenced by changes of 50% the supply air volume. This is caused 40% 30% by the fact that the reduction or 20% increase of the thermal energy of the 10% 0% supply air is partly compensated by -10% 1 CCC. This result in an increase of -20% -30% 22% of the energy consumption for -40% cooling if the supply air volume -50% decreases to 1 ACH and a decrease Ventilation volume [ACH] of 16% if the supply air volume increases to 6 ACH. Cooling CCC Cooling CCC+AHU Heating CCC Heating CCC+AHU Energy consumption [kwh] Figure 5.46: Comparison of energy consumption for 6 different supply air volumes. 5.2 Results: active control strategy of indoor temperature The zone can also be applied with an additional installation component to maintain the indoor temperature between specified ranges. This paragraph describes the simulation results for the situation the indoor temperature is controlled actively to realise a thermal comfort that is in accordance with category B. This simulation has been performed for the reference situation and boundary conditions as described in For the active control a convector unit has been used, which controls the indoor temperature with the supply of additional convective heating or cooling. The following paragraphs describe the difference between the simulation results of the reference situation applied with or without an active control strategy for the indoor temperature Thermal comfort The results for the thermal comfort affirm that the active control strategy of the indoor temperature is capable to maintain a thermal comfort that satisfies category B during the complete simulation period: Figure 5.47 presents that 25% percent of the time the thermal comfort satisfies category A, but during the complete simulation period a category B can be realized; Figure 5.48 shows that all indoor temperatures that occurred during the complete simulation period are within the specified ranges of category B

81 100 Thermal comfort - control strategy 30 min max mean Percentgaes [%] Operative temperature [ o C] Exceeding Amax = 74.4% Limits category A Limits category B Limits category C Exceeding Amin = % self control strategy CCC active control strategy Exceeding Bmax = 0% Exceeding Cmax = 0% Exceeding Bmin = 0% Exceeding Cmin = 0% Category A Category B Category C none Outside temperature [ o C] Figure 5.47: Comparison of thermal comfort for 2 different control strategies of the indoor temperature.48 Figure 5.48: Overview of operative temperatures for the situation the zone is applied with an active control strategy of the indoor temperature Thermal power The use of an additional convector unit has the following effects on the thermal power of both CCC and the supply air (figure 5.49 & 5.50): The thermal power of CCC, for both heating and cooling, increases: The mean heating power increases with 7% to 18,3 W/ m 2 ; The mean cooling power increases with 70% to 28 W/ m 2. The increase of the thermal power of CCC can be addressed to: The use of the convector unit results in higher indoor temperatures in winter and lower indoor temperatures in summer. This results in an increased heat transfer of cooling in winter and heating in summer; The control strategy of the convector unit, because it is possible that the convector unit suddenly starts with a relative large amount of cooling or heating power, whereupon CCC reacts with the transfer of heating or cooling power respectively; The increase of both heating and cooling power of the supply air (including the power of the convector unit) was expected and even the objective of the use of the convector unit, namely: the supply of additional heating and cooling power to maintain the temperature within specified ranges. Heating and cooling power [W/ m²] Thermal power CCC - control strategy 0,5 1,5 2,5 self control strategy CCC Wind direction active control strategy Max. cooling Mean cooling Max. heating Mean heating Heating and cooling power [W/ m²] ,5 1,5 2, Thermal power supply air - control strategy self control strategy CCC Wind direction active control strategy Max. cooling Mean cooling Max. heating Mean heating Figure 5.49: Comparison of thermal power of CCC for 2 different control strategies Figure 5.50: Comparison of thermal power of AHU for 2 different control strategies

82 5.2.3 Energy consumption The effects of the use of an additional convector unit on the energy consumption are (figure 5.51): The total energy consumption for cooling increases with just 6%, while the energy consumption for cooling by CCC decreases with 43%. This means that during cooling situation the energy consumption by CCC decreases, because the convector unit deals with a part of the cooling load; The total energy consumption for heating increases with 22% and the energy consumption by CCC decreases with 52%. In correspondence with the cooling situation, the energy consumption by CCC decreases, because the convector unit deals with a part of the heating load. 30% Energy consumption - control strategy Energy consumption [kwh] 20% 10% 0% -10% 0,5 1,5 2,5-20% -30% -40% -50% -60% self control strategy CCC active control strategy CCC cooling Cooling CCC+AHU CCC heating Heating CCC+AHU Figure 5.51: Comparison of energy consumption for 2 different control strategies. 5.3 Sensitivity analysis The sensitivity analysis was performed to evaluate the sensitivity of the simulation output to changes in individual input parameters. For this analysis the simulation results were used for the situation the indoor temperature is controlled by the self control ability of Concrete Core Conditioning. The analysis has been performed for each of the performance indicators thermal comfort, thermal power and energy consumption. The results of the analysis are presented in the figures 5.52 till

83 Sensitivity of thermal comfort Sensitivity of thermal power CCC facade orientation facade orientation location - horizontal location - vertical location - horizontal location - vertical geometry geometry sun entrance sun entrance construction mass construction mass internal heat gains supply air volume internal heat gains supply air volume increase effect decrease effect cooling - increase effect cooling - decrease effect heating - increase effect heating - decrease effect Figure 5.52: Sensitivity results for thermal comfort (results for category C) Figure 5.53: Sensitivity results for mean thermal power of Concrete Core Conditioning.5.52 The sensitivity of the thermal comfort: The thermal comfort is sensitive for changes in all input parameter values. However, for the parameters facade orientation, vertical location and supply air volume the sensitivity is less than 10%; The results are most sensitive for changes in the input parameters horizontal location, geometry and internal heat gains. Changes in the horizontal location can even result in a decrease of 45% and an increase of 59%. The sensitivity of the thermal power: The cooling power is significantly sensitive for changes in the horizontal location, sun entrance and internal heat gains and this can result in an increase of the thermal power up to 19 W/ m 2. The thermal power can decrease up to 6 W/ m 2 due to changes in the facade orientation; The heating power of CCC is not very sensitive for changes in input parameters. However, the horizontal location of the building is an exception that can result in an increase or decrease of the heating power with 12 W/ m 2 or 13 W/ m 2 respectively. The sensitivity of the total energy consumption: The effect of input parameter changes is very diverse. For the input parameters facade orientation and internal heat gains the sensitivity is limited (< 8%), but for the other input parameters the sensitivity is greater and even up to 50% for the parameter supply air volume; The input parameters horizontal location, vertical location and supply air volume are sensitive for a great increase of the energy consumption. Changes in these parameters can result in an increase of the energy consumption with 35% to 50%; With changes in the horizontal location or the supply air volume it s possible to decrease the energy consumption with about 30%

84 Sensitivity of total energy consumption facade orientation location - horizontal location - vertical geometry sun entrance construction mass internal heat gains supply air volume increase effect decrease effect Figure 5.54: Sensitivity results for total energy consumption (cooling + heating). The results of the sensitivity analysis were ranked to gain insight in the input parameter for which the simulation output is most sensitive. This ranking is based on the absolute difference between the maximum possible decrease and maximum possible increase of the simulation output if a specific input parameter changes. The results of this ranking are presented in table 5.1 and show: The ranking depends on the type of performance indicator for which the analysis has been performed; The horizontal location of a zone within a building and the internal heat gains are always in the top 3 of the ranking. Only for the energy consumption the internal heat gains are not listed in the top 3. Ranking Thermal comfort Energy consumption Thermal power CCC Thermal power CCC cooling heating 1 location horizontal supply air volume internal heat gains location horizontal 2 internal heat gains location horizontal sun entrance geometry 3 geometry location vertical location horizontal internal heat gains 4 sun entrance sun entrance facade orientation sun entrance 5 construction mass geometry geometry supply air volume 6 facade orientation construction mass supply air volume facade orientation 7 supply air volume internal heat gains construction mass construction mass 8 location vertical facade orientation location vertical location vertical Table 5.1: Ranking of sensitivity results for each of the performance indicators. The ranking shows for which input the simulation output is most sensitive (1) or least sensitive (8)

85 5.4 Overall results This chapter describes multiple simulations that have been performed for each of the simulation scenarios. The results of these simulations are described in the paragraphs 5.1 to 5.3. On basis of these results this paragraph describes the overall results of the simulations. These overall results are valid for: The defined reference situation of the input parameters ( 5.1.1); The defined boundary conditions ( 5.1.1). Thermal comfort Concrete Core Conditioning is, for the defined reference situation and boundary conditions, not capable to realize an indoor thermal comfort that satisfies at least the minimum comfort category C of the ISO 7730 [ISO 7730, 2005] during the simulation period of 1 year; The desired thermal comfort can be realized if an additional installation component is applied that maintains the specified indoor temperature range actively; The sun entrance has a linear relationship with the amount of overheating hours. Thermal power The thermal power of CCC, for both heating and cooling, varies on basis of the values of the input parameters and results in the following range of possible values: Cooling: Mean values : W/ m 2 Maximum values : W/ m 2 Heating: Mean values : 4 29 W/ m 2 Maximum values : W/ m 2 Changes in supply air volume don t affect the thermal power (cooling and heating) of Concrete Core Conditioning. Total energy consumption (sum of heating and cooling) The location of the zone within the building has a significance influence on the total energy consumption. For zones along a corner this increase amounts 44%, while this increase amounts 27% for zones on the ground floor and 35% for the top floor; The influence of the parameters facade orientation and internal heat gains on the energy consumption is, with a bandwidth of -4% to 8%, relatively small in relation to the influence of the other input parameters; The application of an additional installation component to maintain the indoor temperature between specified ranges results in an increase of the total energy consumption with 20% Selection of favourable input parameters On basis of the simulation results of each of the scenarios ( 5.1) for every input parameter one or more values were selected that have the potential to be the best option to realize the best achievable indoor thermal comfort. For this selection counts that the defined reference situation and accompanying boundary conditions should be taken into account ( 5.1.1)

86 Input parameter Best option (potentially) Remarks with regard to thermal comfort facade orientation North Comfort differences with other orientations are small (about 6%), but North result in a great decrease of the energy consumption for cooling (-58%). location horizontal internal Internal zone has significance increase of thermal comfort (+59%) in combination with large decrease of total energy consumption (sum of heating and cooling) with 28%. location vertical top floor Comfort differences with other locations are very small (about 5%). The top floor, however, result in an increase of the total energy consumption with 35%. geometry medium, large The ratio between facade surface and CCC surface is the aspect that counts. sun entrance Lower than 15 result in significant decrease of the energy consumption for cooling (up to 64%). construction mass high A high construction mass result in an increase of the total energy consumption (+16%). internal heat gains 35 W/ m 2 Range W/ m 2 has a no influence on the energy consumption. supply air volume 2 ACH 4 ACH The increase of the energy consumption is linear with the increase of the supply air volume. Table 5.2: Overview of the input parameters and their potential best option to realize a good indoor thermal comfort. Note: these potential values count for the reference situation and accompanying boundary conditions as described in

87 6 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS This chapter starts with the description of the comments with regard to the used methodology. The second paragraph describes the conclusions of this thesis and uses the main research question, and its sub questions, as guideline for the formulation. The main question of this thesis is: What are the consequences of applying Concrete Core Conditioning systems for the flexibility of a building concept, now and in the future, and how could this flexibility be increased? The formulated sub questions are: Which aspects represent flexibility? What are the allowed indoor thermal comfort ranges? To what extent flexibility parameters influence the behaviour of Concrete Core Conditioning systems with regard to the indoor thermal comfort? The chapter ends with the description of recommendations that can be used for improvement and further research. 6.1 Discussion This thesis describes the modelling of a dynamic building simulation model that is applied with Concrete Core Conditioning. This model has been used to perform multiple simulations and the results were used to draw conclusions. However, some aspects have to be taken into account. The realized building simulation model is a combination of multiple subsystems. The main subsystems are the multi-zone building model Hambase and the Concrete Core Conditioning model. HamBase [Wit, 2006; TUe, 2009] is a validated model that has been developed by the TU/e. The model of Concrete Core Conditioning is completely based on scientific literature which describes the mathematic model of Concrete Core Conditioning. The combination of these subsystems resulted in the developed building simulation model. This model hasn t been validated, because measurements to make this validation possible were outside the scope of this thesis. Therefore, the results produced by the developed building simulation model could differ from results from practice. The thermal comfort has been evaluated on basis of indoor temperature ranges that are equivalents of PMV values. The PMV values are standardized in the ISO 7730 [ISO 7730, 2005] and defined for three different comfort categories A, B and C. For the calculation of the PMV values into equivalent operative temperatures has been made use of the starting points as described in the ISO However, for the thermal resistance of clothing has been made use of the outdoor temperature related relationship found by De Carli et al. [De Carli, 2007]. This resulted in three operative temperature ranges, equivalent to the comfort categories A, B and C, and related to the outdoor temperature. These ranges were used to evaluate the thermal comfort. In practice, however, the evaluation of thermal comfort is often based on the standardized operative temperature equivalents (examples of table A.5, ISO 7730) and an evaluation on basis of these operative temperatures will result in other conclusions. However, it

88 should be noted that the standards doesn t include a method to calculate operative temperature equivalents for mid-season periods. The simulations have been performed on basis of a defined reference situation of the input parameters and accompanying boundary conditions. The simulation results, therefore, only counts for these conditions. This means: The simulations should be performed again if the reference situation or boundary conditions change; The results of the performed simulations can change if the values of the reference situation or boundary conditions are changed. Finally, the simulation results have been evaluated on basis of changes in individual parameters. Multiple changes in input parameter values could result in different simulation results, but this insight is not available. 6.2 Conclusions A building with flexibility, or more specifically technical flexibility, has the ability to accommodate the desired changes of the working environment by means of two different strategies: layout and function flexibility. Each of these strategies can influence the parameters as presented in table 6.1. Relating these parameters to utilization and building properties result in a list of parameters that represent flexibility (table 6.2). Strategy Influenced parameters by flexibility strategy Layout flexibility the zone s geometry the zone s orientation (vertical or horizontal) Function flexibility the zone s function the number of functions within a building Table 6.1: Flexibility strategies and their area of influence. Utilization properties Building properties Internal heat gains External heat gains Construction properties Orientation persons lighting equipment facade insulation sun entrance air infiltration geometry construction mass thermal properties facade orientation location in building horizontal vertical Table 6.2: Parameters that influence the thermal comfort in a zone and related to building flexibility. The thermal comfort within buildings is standardized in the ISO 7730 [ISO 7730, 2005]. Within this standard the thermal comfort is standardized by PMV values that are defined for 3 different comfort categories: A, B and C. These comfort categories can be calculated to equivalent operative temperatures by using the starting points that are also described in the ISO However, this standard doesn t describe the thermal insulation of clothing during mid-season period. De Carli et al. [De Carli, 2007] found a relationship for the clothing insulation in relation to the outdoor temperature. On basis of this relationship the standardized PMV values can be calculated to equivalent operative temperatures that are related to the outdoor temperature. These operative temperature ranges are presented in figure

89 Operative temperature [ o C] Outside temperature [ o C] Cat. A - min Cat. A - max Cat. B - min Cat. B - max Cat. C - min Cat. C - max Figure 6.1: Operative temperature ranges as function of the outside temperature. The ranges are equivalents of the PMV categories A, B and C [ISO 7730, 2005] and based on De Carli s et al. relationship for the behaviour of clothing insulation [De Carli, 2007]. On basis of the definition of the flexibility parameters and the thermal comfort ranges the behaviour of Concrete Core Conditioning has been researched and this resulted in the following conclusions in relation to thermal comfort: The thermal comfort realized by Concrete Core Conditioning is sensitive for all changes in flexibility parameter values. For the parameters facade orientation, vertical location and supply air volume, however, the sensitivity is less than 10%; The solely use of Concrete Core Conditioning will not result in an indoor thermal comfort that satisfies the comfort categories A, B, or C of the ISO 7730 [ISO 7730, 2005] during a complete simulation period of 1 year. For the chosen reference situation and boundary conditions even a category C cannot be realized. Furthermore, the self control ability of Concrete Conditioning is not appropriate to adapt its thermal power to every possible situation in relation to flexibility. The use of an additional component makes it possible to maintain the indoor temperature between specified ranges, but result in an increase of the total energy consumption with 20%; If Concrete Core Conditioning is applied the values of the flexibility parameters as mentioned in table 6.3 have the potential to be the best option for the realization of the best achievable thermal comfort. The flexibility parameters in this table are, on basis of the results of a sensitivity analysis, ranked from most influence to least influence flexibility parameter. Note: the above mentioned conclusions count for the reference situation and accompanying boundary conditions as described in

90 Ranking Flexibility parameter Best option (potentially) with regard to thermal comfort Remarks 1 location horizontal internal Internal zone has significance increase of thermal comfort (+59%) in combination with large decrease of total energy consumption (sum of heating and cooling) with 28%. 2 internal heat gains 35 W/ m 2 Range W/ m 2 has a no influence on the energy consumption. 3 geometry medium, large The ratio between facade surface and CCC surface is the aspect that counts. 4 sun entrance Lower than 15 result in significant decrease of the energy consumption for cooling (up to 64%). 5 construction mass high A high construction mass result in an increase of the total energy consumption (+16%). 6 facade orientation North Comfort differences with other orientations are small (about 6%), but North result in a great decrease of the energy consumption for cooling (-58%). 7 supply air volume 2 ACH 4 ACH The increase of the energy consumption is linear with the increase of the supply air volume. 8 location vertical top floor Comfort differences with other locations are very small (about 5%). The top floor, however, result in an increase of the total energy consumption with 35%. Table 6.3: Overview of potential best values for each of the flexibility parameters with regard to the realization of the best achievable indoor thermal comfort. The flexibility parameters are ranked from most to least influencing parameter. Concluding a building concept that includes Concrete Core Conditioning has to cope with the restrictions that count for the values of the utilization and building parameters in order to realize a good indoor thermal comfort (table 6.3). For future changes of the working environment it has to be taken into account that changes in flexibility parameters most likely result in changes of the thermal comfort. Therefore, future changes of the working environment can be limited accommodated by Concrete Core Conditioning without loss of thermal comfort. The application of an additional installation component, e.g. a convector for both heating and cooling, makes the concept of Concrete Core Conditioning suitable for integration with the current and future building and utilization parameters. The application of an additional installation component increases the total energy consumption, but still a reasonable part (> 24%) is used by Concrete Core Conditioning. Therefore, Concrete Core Conditioning can be used in flexible building concepts, but it requires the application of additional installation components for the supply of additional cooling and heating power. The combination of Concrete Core Conditioning and an additional installation component result in a climate system that is suitable to accommodate changes in the working environment without loss of thermal comfort. This system result in an increase of the energy consumption, but its applicability in combination with renewable energy sources lets this system still have the potential to be an energy efficient climate system

91 6.3 Recommendations For both improvement of the results and further research the following aspects are recommended: The developed building simulation model hasn t been validated. It s recommended to validate the building simulation model with measurements of a Concrete Core Conditioning system. This validation will give insight in the correctness of the model and, besides, create an opportunity to make Concrete Core Conditioning an integral subsystem of HamBase. The thermal comfort has been evaluated on basis of operative temperature equivalents of standardized PMV values. To calculate this equivalent indoor temperature there has been made use of a found relationship of De Carli et al [De Carli, 2007]. In practice the indoor thermal comfort is often evaluated on basis of the indoor operative temperature equivalents as described in the ISO 7730 [ISO 7730, 2005] (examples). Insight in the difference between the evaluation of thermal comfort on basis of the relationship of De Carli et al. or the standard based indoor operative temperature equivalents are useful for the interpretation of the simulation results of this thesis. Control strategies for both the water inlet of Concrete Core Conditioning and the supply air temperature were set as boundary conditions. It s recommended to gain insight how these strategies could be changed to improve the simulation results. The effect of changes in multiple input parameters together hasn t been evaluated. It s recommended to gain insight in the effect of these multiple changes to gain more insight in a possible optimum, or range of values, for which the Concrete Core Conditioning performs best in relation to the realization of a good indoor thermal comfort. This thesis describes the energy consumption of both Concrete Core Conditioning and the Air Handling Unit. These are absolute values and gain insight in the contribution of each of these systems to the total energy consumption. However, the amount of primary energy needed for heating and cooling hasn t been calculated. It s recommended to add this calculation, because it gains insight in the energy efficiency of Concrete Core Conditioning. With regards to the simulation model the following can be recommended for improvement: The system of Ordinary Differential Equations of the Concrete Core Conditioning model consists of 3 sets: ground floor, intermediate floor and roof. A simplification will result in a significant decrease of the calculation time; The location of the piping system is fixed, namely the second layer of the CCC construction. It will be user-friendly if this location can be easily changed; The attendance profile has to be filled in on 2 locations: within the CCC system and within Simulink. A simplification into 1 location makes the model more userfriendly; Hambase divides the heat flow of heating and cooling systems into a convective and radiant part by using a convection factor. For the heat flow of the CCC construction a fixed value is used, but this can be improved by the

92 implementation of a variable convection factor which is based on the variable Heat Transfer Coefficients of the CCC construction

93 7 REFERENCES Articles [Boerstra, 2003]: Boerstra, A.C, J.L. Leijten, Binnenmilieu en productiviteit: eindelijk harde cijfers. Verwarming & Ventilatie, juni 2003, pages [Bruggema, 2007]: Bruggema, H.M., Betonkernactivering, klimaatplafonds, wand- en vloerverwarming. TVVL Magazine, maart 2007, pages [Cauberg, 2003]: Cauberg, J.J.M., Ruimte-akoestiek bij vloerkoeling in kantoren. Bouwwereld 1, 2003, pages [De Carli, 2007]: De Carli, M., Bjarne W. Olesen, A. Zarrella, R. Zecchin, People s clothing behaviour according to external weather and indoor environment. Building and Environment, 2007, page [Eijdems, 2007]: Eijdems, H.H.E.W., Praktijkervaring met thermisch actieve bouwdelen. TVVL Magazine, maart 2007, pages [Kobayashi, 2003]: Kobayashi, A., K. Kohri, A study on the thermal response characteristics of the floor of hydronic floor heating systems. Eight International IBPSA Conference, 2003, pages [Lehmann, 2007]: Lehmann, Beat, Viktor Dorer, Markus Koschenz, Application range of thermally activated building systems tabs. Energy and Buildings 39, 2007, pages [Lomas, 1992]: Lomas, K.J., Herbert Eppel, Sensitivity analysis techniques for building thermal simulation programs. Energy and Buildings, 1992, page [Olesen, 2002]: Olesen, Bjarne W., Klaus Sommer, Björn Düchting, Control of Slab Heating and Cooling Systems Studied by Dynamic Computer Simulations. ASHRAE Transactions, July [Olesen,2004]: Olesen, Bjarne W., Radiant heating and cooling by embedded waterbased systems. Technical University of Denmark, International Centre for Indoor Environment and Energy, [Olesen, 2002]: Olesen, Bjarne W., Sind kalte Fensterflächen heute überhaupt ein Problem für Behaglichkeit?. Velta Kongress, [Rijksen, 2007]: Rijksen, R., K. Wisse, Halvering koudeopwekking door betonkernactivering (I). Verwarming & Ventilatie, 2007, pages [Rijksen, 2007]: Rijksen, R., K. Wisse, Halvering koudeopwekking door betonkernactivering (II). Verwarming & Ventilatie, 2007, pages [Schrevel, 2002]: Schrevel, R.A.M. de, Betonkernactivering, een nieuwe manier van gebouwklimatisering. Verwarming & Ventilatie, juli/ augustus 2002, pages

94 [Sommer, 2002]: Sommer, Klaus, Untersuchung verschiedener Regelstrategien für die Betonkernaktivierung mit Hilfe der Computersimulation. Velta Kongress, [Weitzmann, 2005]: Weitzmann, Peter, Svend Svendsen, Detailed measurements and modelling of thermo active components using a room size test facility. Technical University of Denmark, International Centre for Indoor Environment and Energy, Reports and books [Boerstra, 2006]: Boerstra, A.C., J.L. Leijten, L. Haans, Literatuuronderzoek gebouwgebonden gezondheid, comfort, productiviteit en ziekteverzuim in relatie tot energiegebruik, Rotterdam, BBA. [Buitenhuis, 2007]: Buitenhuis, J.J., A.M.J. Notenboom, Thermisch actieve vloeren, koelen en verwarmen met betonkernactivering, Rotterdam, SBR. [ISO 7730, 2005]: ISO 7730 Ergonomics of the thermal environment, Geneva, International Organization for Standardization (ISO). [ISSO, 1998]: ISSO publicatie 48, Klimaatplafonds/ koelconvectoren, Rotterdam, ISSO. [Macdonald, 2002]: Macdonald, I.A., Quantifying the effects of uncertainty in building simulation, Glasgow, University of Strathclyde. [SenterNovem, 2008]: Nederlands afval in cijfers, gegevens , Utrecht, SenterNovem. [Recknagel, 2005]: Recknagel, H., E. Sprenger, Taschenbuch für Heizung und Klimatechnik, München, Oldenbourg Industrieverlag München. [Wit, 2001]: Wit, M.S. de, Uncertainty in predictions of thermal comfort in buildings, Delft, Technische Universiteit Delft. [Wit, 2006]: Wit, M. de, HamBase, Heat Air and Moisture model for Building And Systems Evaluation, Eindhoven, Eindhoven University of Technology. [Koschenz, 2000]: Koschenz, M., B. Lehmann, Thermoaktive Bauteilsysteme TABS, Dübendorf, EMPA. [CR 1752, 1998]: CR 1752 Ventilation for buildings Design criteria for the indoor environment, Brussels, European Committee for Standardization (CEN). [EN 15251, 2007]: EN Indoor environmental input parameters for design and assessment of energy performance of building addressing indoor air quality, thermal environment, lighting and acoustics, Brussels, European Committee for Standardization (CEN). Software [Matlab, 2006]: Matlab, The Language of Technical Computing, version (R2006b). The Mathworks,

95 [Simulink, 2006]: Simulink, Dynamic System Simulation for Matlab, version 6.5 (R2006b). The MathWorks. Internet sources [VROM, 2009]: Dutch Ministry of Housing Spatial Planning and the Environment ( [ECN, 2009]: Energy Research Centre of the Netherlands ( [IFD, 2009]: IFD Platform ( [WBDG, 2009]: Whole Building Design Guide, National Institute of Building Sciences ( [TUe, 2009]: Eindhoven University of Technology, unit Building Physics & Systems (

96 Flexibility & Concrete Core Conditioning Synonyms or a contradiction? - Appendix - 15 December 2009 Final Report

97

98 Flexibility & Concrete Core Conditioning Synonyms or a contradiction? - Appendix - Document title Flexibility & Concrete Core Conditioning Synonyms or a contradiction? Program Eindhoven University of Technology Master program Building Services Author Jeroen Rietkerk Studentid Committee members prof. dr. ir. J.L.M. Hensen - TU Eindhoven dr. ir. ing. A.W.M. van Schijndel - TU Eindhoven ir. J.P. Ruchti - Royal Haskoning Graduation company Royal Haskoning Division Building Services - Rotterdam Status Final Report Date 15 December 2009

99

100 CONTENTS OF APPENDIX (1) Page ANNEX A 1 Standard based design criteria for the thermal environment ANNEX B 5 Methods to evaluate thermal comfort conditions ANNEX C 9 Operative temperature equivalents of standardized PMV values ANNEX D 17 Modifications to the multi zone model HamBase ANNEX E 27 Modelling Concrete Core Conditioning ANNEX F 39 Modelling HVAC system ANNEX G 47 Modelling HTC system ANNEX H 51 The CCC building simulation model: starting guide ANNEX I 59 Simulation parameters & boundary conditions ANNEX J 65 Calculation of input parameter values ANNEX K 73 Simulation results ANNEX L 79 Matlab code: Modified HamBase M-files ANNEX M 127 Matlab code: S-function Concrete Core Conditioning system Annex page i

101 CONTENTS OF APPENDIX (2) Separately, a CD with the following digital information is part of this report: This report in digital format; Simulation models of systems: HamBase: The original version, dated October 2006; The modified version; Concrete Core Conditioning The original version, dated September 2009; The version used for verification; HVAC The original version; The version used for verification; Heat Transfer Coefficient The original version; The version used for verification; The CCC building simulation model: The basis model; The basis model used to run simulation series programmatically; The basis model with an active control of indoor temperature. Annex page ii

102 Annex A Standard based design criteria for the thermal environment Annex page 1

103 2

104 Standard based design criteria for the thermal environment Standard International standard - ISO 7730:2005 European standard - NEN-EN 15251:2007 Comfort Category A B C I II III IV Aspects Unit Thermal comfort General thermal comfort Thermal state of the body as a whole PMV [-] -0,2 < PMV < 0,2-0,5 < PMV < 0,5-0,7 < PMV < 0,7-0,2 < PMV < 0,2-0,5 < PMV < 0,5-0,7 < PMV < 0,7 PMV < -0,7 or PMV > +0,7 PPD [%] < 6 < 10 < 15 < 6 < 10 < 15 > 15 Operative temperatures 1) office summer [ o C] 24,5 +/- 1,0 24,5 +/- 1,5 24,5 +/- 2,5 max 25,5 max. 26 max winter [ o C] 22,0 +/- 1,0 22,0 +/- 2,0 22,0 +/- 3,0 min. 21,0 min. 20 min school summer [ o C] 24,5 +/- 1,0 24,5 +/- 1,5 24,5 +/- 2,5 max 25,0 max. 26 max winter [ o C] 22,0 +/- 1,0 22,0 +/- 2,0 22,0 +/- 3,0 min. 21,0 min. 20 min hospital - ward 4) [ o C] 21,5-25,5 Local thermal discomfort Floor temperature [ o C] not described not described not described not described Radiant temperature asymmetry warm ceiling [ o C] < 5 < 5 < 7 not described not described not described not described cool wall [ o C] <10 < 10 < 13 idem idem idem idem cool ceiling [ o C] < 14 < 14 < 18 idem idem idem idem warm wall [ o C] < 23 < 23 < 35 idem idem idem idem Vertical air temperature difference 5) [ o C] < 2 < 3 < 4 not described not described not described not described Humidity [%] 2) 2) 2) 3) 3) 3) not described Draught rate [%] < 10 < 20 < 30 not described not described not described not described Maximum mean air velocity 6) summer [m/s] 0,12 0,19 0,24 not described not described not described not described winter [m/s] 0,10 0,16 0,21 idem idem idem idem Notes 1) These are recommended values according to table A.5 [ISO 7730] and table A.2 [NEN-EN 15251] 2) When Top < 26 o C and activity < 3,2 met, the influence of humidity on thermal comfort is limited. 3) The humidification of indoor air is usually not needed. Humiditiy has only a small effect on thermal sensation and perceived air quality. Very low humidity (< 15% - 20%) causes dryness and irritation of eyes and air ways. 5) Thermal comfort based on PMV +/- 0,5 according Annex page to "Thermische 3 behaaglijkheid in verpleeghuizen in Nederland in de zomersituatie. PRelude B.V, 14 juni 2002." 6) Applies for 0,1 m and 1,1 above floor. 7) This is an example design criteria (table A.5): turbulence intensity = 40%, air temperature is equal to operative temperature, relative humidty of 60% in summer and 40% in winter.

105 Annex page 4

106 Annex B Methods to evaluate thermal comfort conditions Annex page 5

107 6

108 Methods to evaluate thermal comfort conditions Method Description Remark Source: International standard - ISO 7730:2005 Long-term evaluation of general thermal comfort - method A Calculate the number or percentage of hours during the hours the building is occupied, the PMV or the operative temperature is outside a specified range. This a good parameter if the operative temperature is applied, because it is understandable for persons that has less knowledge about comfort evaluation and it can be verified in practice by measurements. - method B - method C - method D - method E The time during which the actual operative temperature exceeds the specified range during the occupied hours is weighed with a factor which is a function of how many degrees the range has been exceeded. The time during which the actual PMV exceeds the comfort boundaries is weighed with a factor which is a function of the PPD. The average PPD over time during the occupied hours is calculated. The PPD over time during occupied hours is summed. Weighed factors aren't very clear to communicate with persons who don't have knowledge about comfort criteria. Therefore, this method won't be chosen. Weighted factors aren't very clear to communicate with persons who don't have knowledge about comfort criteria. Therefore, this method won't be chosen. This is a parameter that can be calculated, but it doesn't indicate much. More important are the minuman and maximum values which occur during the occupied hours. Are they acceptable and what about the PMV during the start of the occupied hours? Not a good indicator, because no one has any feeling with this parameter. Source: European standard - NEN-EN 15251:2007 Thermal evaluation - simple indicator - method A: percentage outside the range - method B: degree hours criteria To evaluate the performance of the whole building representative rooms or spaces have to be simulated. The building meets the criteria of a specific category if the rooms representing 95% of building volume meet the criteria of the selected category. Calculate the number or % of occupied hours when the PMV or the operative temperature is outside a specified range. The time during which the actual operative temperature exceeds the specified range during the occupied hours is weighed by a factor which is a function depending on by how many degrees, the range has been exceeded. The idea of my thesis is to find out if it's possble to realize a good thermal comfort in all rooms of a building. Therefore, the criteria of 95% is not a good starting point for my thesis. Same as method A of ISO Same as method B of ISO method C: PPD weighed criteria The time during which the actual PMV exceeds the comfort boundaries is weighed by a factor which is a function of the PPD. Same as method C of ISO Acceptable deviations Recommendend: during 3% or 5% of the occupied hours it's allowed to be outside the limits ot he specified category. A parameter that can be used to evaluate the performance indicator, indedepended the type of performance indicator is selected. Source: Olesen, B.W., Klaus Sommer, Control of slab heating and cooling systems, studied by dynamic computer simulations. ASHRAE 2002-HI Selected criteria to compare variants: - operative temprature range The % of occupied hours is calculated when the operative temperature is in a specific range (histogram). Constant clo-values are assumed, so 0,5 clo in summer and 1,0 clo in winter. Same as method A of ISO temperature drift during occupied hours The temperature drift which persons are exposed to during the whole working day, so not per hour! This is a parameter that isn't mentioned in the standards and therefore it will not be used as a comfort indicator. - energy consumption - 1 week analysis Energy consumption for cooling and heating of the CCC construction. A line graph of 1 week with the outside and operative temperature to get more insight in the Annex behaviour page of the system 7 during the day. A simple but clear parameter to evaluate the energy consumption.. Gives a good insight in the functioning of the system.

109 Annex page 8

110 Annex C Operative temperature equivalents of standardized PMV values Annex page 9

111 Annex page 10

112 The international standard ISO 7730 [ISO 7730, 2005] describes the standardized PMV criteria for each of the comfort categories A, B and C (table C.1). These criteria have been converted to equivalent operative temperature ranges: a bandwidth between a minimum and maximum operative temperature that counts for the assumed design conditions. Comfort category PMV [ - ] A -0,2 < PMV < +0,2 B -0,5 < PMV < +0,5 C -0,7 < PMV < +0,7 Table C.1: Standardized PMV criteria for each of the comfort categories A, B and C [ISSO, 7730] Method The conversion of the standardized PMV criteria to equivalent operative temperatures has been executed using the following method: 1. Definition of the operative temperature The operative temperature is represented by using the following relationship: = [1] where: : operative temperature [ C] : air temperature [ C] : mean radiant temperature [ C] 2. Selection of the required equations for conversion The equivalent operative temperatures have been calculated by using the PMV equations as described in the ISO These equations are inserted on the last page of this appendix. The method used to use these equations to calculate the operative temperature is described in step Definition of parameters The PMV equations have the following parameters: : metabolic rate [W/ m 2 ] : effective mechanical power [W/ m 2 ] : clothing insulation [m 2 / K W] : air temperature [ C] : mean radiant temperature [ C] : relative air velocity [m/ s] : relative humidity [Pa] 4. Assumption of design conditions The following assumptions are made for each of the parameters: A metabolic rate of 1,2 met that corresponds with 69,8 W/ m 2 ; An effective mechanical power of 0 W/ m 2 ; Annex page 11

113 The mean radiant temperature ( is equal to the air temperature (. This makes the operative temperature equal to the air and radiant temperature; The relative air velocity is derived from table A.5 from the ISO 7730 [ISSO, 7730]. This table presents air velocities for both winter and summer. For mid season the average value of these velocities is applied. The relative humidity is derived from the assumptions made in table A.5 from the ISO 7730 [ISSO, 7730]. These assumptions include a value for both winter and summer. For mid season the average value of these humidity s is applied. Taking into account the assumptions for the relative air velocity and the relative humidity the outside temperatures (T e ) for each of the seasons are defined as: winter : -10 C T e 5 C mid season : 5 C < T e < 15 C summer : 15 C T e 35 C The clothing insulation is a function of the outside temperature based on the relationship found by De Carli et al. [De Carli et al., 2007]. The applied relationship counts for the mean clo value for mechanically ventilated buildings and is described as: = These assumptions resulted in the design conditions which the equivalent operative temperature ranges have been calculated for. An overview of these conditions is presented in table C.2. Parameter Value metabolic rate [met] or [W/m 2 ] 1,2 or 69,8 effective mechanical power [W/m 2 ] 0 clothing insulation [clo] = relative air velocity comfort category A comfort category B comfort category C [m/s] winter 0,10 0,16 0,21 summer 0,12 0,19 0,24 relative humidity [%] mid season 0,11 0,175 0,22 Table C.2: Assumed design conditions used for the conversion of the PMV into equivalent operative temperature ranges. 5. Calculation of the equivalent operative temperatures The clothing insulation as function of the outside temperature meant that the operative temperature had to be a function of the outside temperature too. Therefore, the objective of the calculations was to convert the minimum and maximum PMV of the standardized PMV criteria into equivalent operative temperatures that are a function of the outside temperature. Annex page 12

114 The calculation contained the following steps: Calculation of the PMV for all combinations of the outside temperature and the operative temperature using the design conditions of table C.2. For the outside and operative temperature counts: outside temperature range : -10 C to 35 C, step size: 1 C operative temperature range : 16 C to 30 C, step size: 0,1 C The datasheet with the calculated PMV values was filtered by selecting all combinations of the outside and operative temperature with a PMV that satisfied the standardized minimum and maximum PMV values of each of the comfort categories A, B or C; The selected combinations were used to create a figure that presents the operative temperatures for each of the comfort categories as function of the outside temperature; The created figure was used to derive a linear trend line, including its equation, for each of the minimum and maximum operative temperatures of the comfort categories A, B and C. These equations are used to represent the operative temperature as function of the outside temperature. Results The calculation results are presented in figure C.1 that shows the PMV for each of the combinations of the outside and operative temperature. Based on these results the combinations were derived that satisfy the standardized minimum and maximum PMV of the comfort categories A, B and C [ISSO, 7730]. This selection is presented in figure C.2 and shows the minimum and maximum operative temperatures as function of the outside temperature for each comfort category. Figure C.1: Calculated PMV values for the combinations of the outside and operative temperatures. The calculations are executed for the design conditions presented in table C Figure C.2: Combinations of operative and outside temperatures that are equivalent with the standardized PMV criteria for each of the comfort categories A, B and C. Operative temperature [ o C] Outside temperature [ o C] Cat. A equivalents Cat. B equivalents Cat. C equivalents Annex page 13

115 The results in figure C.2 are used to derive a trend line, including its equation, for the allowable minimum and maximum operative temperatures for each of the comfort categories. The derived equations represent the equivalent operative temperatures of the standardized PMV criteria and are shown in table C.3. These equations are visualized in figure C.3. Comfort category PMV Operative temperature range Minimum Maximum [ - ] [ C] [ C] A -0,2 < PMV < +0,2 22,2 + 0,054 T e 23,9 + 0,043 T e B -0,5 < PMV < +0,5 21,6 + 0,063 T e 25,5 + 0,035 T e C -0,7 < PMV < +0,7 21,2 + 0,068 T e 26,5 + 0,030 T e Table C.3: The minimum and maximum operative temperatures as function of the outside temperature (T e) and equivalent tot the standardized PMV [ISSO, 7730] Operative temperature [ o C] Outside temperature [ o C] Cat. A - min Cat. A - max Cat. B - min Cat. B - max Cat. C - min Cat. C - max Figure C.3: Operative temperature ranges as function of the outside temperature. The ranges are equivalents of the PMV categories A, B and C [ISSO 7730, 2005] and based on De Carli s et al. relationship for the behaviour of clothing insulation [De Carli et al., 2007]. Annex page 14

116 Calculation of PMV The PMV can be calculated by using the equations below that are derived from the ISO 7730 [ISSO, 7730]. = ) ( 0(, ( ( + [2] = ( 7 9 ( ( 1 [3] = (, (, ( ( (, ( [ [4] = 3 ( [ [5] where: : metabolic rate [W/ m 2 ] : effective mechanical power [W/ m 2 ] : clothing insulation [m 2 / K W] : clothing surface area factor [ - ] : air temperature [ C] : mean radiant temperature [ C] : relative air velocity [m/ s] : partial pressure of water vapour [Pa] : convective heat transfer coefficient [W/ m 2 K] : clothing surface temperature [ C] The water vapour pressure can be calculated on basis of the relative humidity using the following relationships: = 2 8 = ] [6] ] = ) ) 5 [ [7] where: : relative humidity [ - ] : water vapour partial pressure [Pa] ] : water vapour saturation pressure [Pa] : air temperature [ C] Annex page 15

117 Annex page 16

118 Annex D Modifications to the multi zone model HamBase Annex page 17

119 Annex page 18

120 The building simulation model modelled for this thesis consists of 3 different systems. The in- and output of each of these systems are connected with each other to result in the CCC building simulation model. One of these systems is HamBase: a multi zone model for heat and vapour flows in buildings. This appendix describes the changes made to the in- and output of Hambase in order to make the connection between the systems possible. Original HamBase version As basis for the modification the Hambase version dated October 2006 [Eindhoven niversity of Technology] was used. This model consists of a combination of Matlab and Simulink files. The Simulink file is presented in figure D.1 and shows the in- and output of the model that is also presented in table D.1. Figure D.1: Simulink model of HamBase Input Output Symbol Description Unit Symbol Description Unit Q plant Heat flow released in zone W T air Indoor air temperature C G plant Vapour flow released in zone kg/ s T comfort Operative temperature C Table D.1: In and output of Hambase, version October 2006 R h Indoor relative humidity - T e Outdoor temperature C RV e Outdoor relative humidity - Not all files that belong to the original version of HamBase were modified. The files that were modified are presented in table D.2. To prevent confusion with the original Hambase files these file were renamed. These names are also presented in table D.2. Original HamBase file Renamed file BUILDmod1.mdl BUILDmod1_mod.mdl Hambasefun5.m Hambasefun5_mod.m startexample1.m startexample1_mod.m Wavoinit1205.m Wavoinit1205_mod.m wavosimulinksfun.m wavosimulinksfun_mod.m Wavovaru0606.m Wavovaru0606_mod.m Zonfunf2.m Zonfunf2_mod.m Table D.2: Overview of modified Hambase files, including their renamed file Annex page 19

121 Required changes to the in- and output As mentioned in the following modifications are required to the in- and output of the Hambase model: Changes to the input Hambase treats radiant and convective heat differently and, therefore, HamBase requires the definition of a convection factor: a factor that divides the input heat flow into a radiant and convective part. However, just 1 convection factor can be defined for each zone separately. As HamBase is connected to 2 different systems for heating and cooling, Concrete Core Conditioning and HVAC, it is needed to define a convection factor for 2 different heating and cooling systems. Therefore, the input is expanded with an extra heat flow input, including its own convection factor. Changes to the output For the connection between the output of HamBase and the input of the other systems the following changes were made to the output: The operative temperature was replaced by the mean wall temperature. The operative temperature is calculated in the Concrete Core Conditioning model, so also the surface temperature of the floor and walls are taken into account; The following outputs were added: The total wall surface and used to calculate the mean radiant temperature; The solar energy that is released in the zone. This solar energy includes the effect of the dimensions and properties of the window; The solar radiation on a horizontal outdoor surface. This radiation is used to simulate the heat balance of a roof applied with Concrete Core Conditioning. Modifications to HamBase: step by step Hereafter, the modifications are described that were made to the original HamBase files. These modifications are the changes made to the Matlab code and described for each file separately and ordered per change, namely: Changes due to renamed files; Changes to the input; Changes to the output mean wall temperature; Changes to the output total wall surface; Changes to the output solar heat released in zone; Changes to the output solar heat on outdoor horizontal surface; Changes to configuration of in- and output structure. The Matlab code of each of these file is enclosed in appendix L. The changes made to these files in relation to the original version are highlighted in yellow. Changes due to renamed files In order to make specific calculations some files are enclosed in other HamBase files. As some of the files were renamed, some of the enclosed filenames had to be changed too. This resulted in the following changes for each file: File: BUILDmod1_mod.mdl Function block parameters Parameters use startexample1_mod Function block parameters S-function name wavosimulinksfun replaced by wavosimulinksfun_mod Annex page 20

122 File: startexample1_mod.m line 517 Hambasefun5 replaced by Hambasefun5_mod File: Wavoinit1205_mod.m line 1 Wavoinit1205 replaced by Wavoinit1205_mod File: wavosimulinksfun_mod.m line 75 Wavoinit1205 replaced by Wavoinit1205_mod File: Wavovaru0606_mod.m line 19 Zonfunf2 replaced by Zonfunf2_mod The file wavosimulinksfun.m originally contained a wrong reference to Wavovaru1205, therefore, the following changes were made: File: wavosimulinksfun_mod.m line 124 Wavovaru1205 replaced by Wavovaru0606_mod line 287 Wavovaru1205 replaced by Wavovaru0606_mod Changes to the input For the realisation of an extra heat flow as input of HamBase, including its own convection factor, the following changes were made: File: Hambasefun5_mod.m line 36 CFset(kzone) = BAS.convfac{k}(2) replaced by CFset(kzone) = BAS.convfac{k}(3) line 37 CFint(kzone) = BAS.convfac{k}(3) replaced by CFint(kzone) = BAS.convfac{k}(4) line 39 added: CFhad(kzone) = BAS.convfac{k}(2); line 566 added: Control.CFhad = CFhad; File: startexample1_mod.m A convection factor for the extra heating/ cooling system is introduced in this file, namely CFhad. To introduce the new convection factor CFhad the original matrix BAS.convfac was rearranged and expanded with the new convection factor, so the changes are: line column 1: CFh column 2: CFhad column 3: CFset column 4: CFint File: Wavoinit1205_mod.m line 23 added: CFhad = Control.CFhad ; line 175 added: Elan.Facpad = CFhad - (1 - CFhad).*hcv / hrx; Annex page 21

123 File: wavosimulinksfun_mod.m The introduced convection factor CFhad is used in combination with a new, extra, input in the Simulink model. This new input is used as input for the heat flow of an extra heating and cooling system. The convection factor CFhad should divide this heat flow into a convective and radiant part. To make this possible several changes are required. The main changes are: Introduction of P.fplantad as a new input of the Simulink model; Modifications to the differential equations. The changes that were made to each line of the file are: line 66 added: Global Facpad line 128 added: P.fplantad = 0; line 172 added: Facpad = Elan.Facpad; line 195 added: Global Facpad line 211 added: P.fplantad = u(zonetot + [1:zonetot]) line 212 P.Gextra = u(zonetot + [1:zonetot]) replaced by P.Gextra = u(2*zonetot + [1:zonetot]); line 219/220 Tx=( diag(lxa+ldeta+lgtot+lx1+lx2) - Ldet )\... (Lxa.*Ta+Lx1.*Tp+Lx2.*Tq+fgtransU+... fzonab+figainx+lgtot.*tglaseu+(1-facp).*p.fplant); replaced by Tx=( diag(lxa+ldeta+lgtot+lx1+lx2) - Ldet )\... (Lxa.*Ta+Lx1.*Tp+Lx2.*Tq+fgtransU+... fzonab+figainx+lgtot.*tglaseu+(1-facp).*p.fplant + (1 - Facpad). * P.fplantad); line 248 xdot3=(1./ca ).*( -Lv.*(Ta-TeU) - Lxa.*(Ta-Tx)+ Link*Ta + figaina + Facp.*P.fplant); replaced by xdot3=(1./ca ).*( -Lv.*(Ta-TeU) - Lxa.*(Ta-Tx)+ Link*Ta + figaina + Facp.*P.fplant + Facpad.*P.fplantad); line 350 added: Global Facpad line 362/363 Tx=( diag(lxa+ldeta+lgtot+lx1+lx2) - Ldet )\... (Lxa.*Ta+Lx1.*Tp+Lx2.*Tq+fgtransU+... fzonab+figainx+lgtot.*tglaseu+(1-facp).*p.fplant); replaced by Tx=( diag(lxa+ldeta+lgtot+lx1+lx2) - Ldet )\... (Lxa.*Ta+Lx1.*Tp+Lx2.*Tq+fgtransU+... fzonab+figainx+lgtot.*tglaseu+(1-facp).*p.fplant + (1 - Facpad).* P.fplantad); Changes to the output mean wall temperature The following changes were made to get the mean wall temperature as an output: File: wavosimulinksfun_mod.m line 201 equation of tfrac copied to line 354 line 215 equation of fgtransu copied to line 355 line 221 equation of Tw copied to line 364 line 352 added: Global Lrcvx fgtransoud Pu Annex page 22

124 Changes to the output total wall surface The following changes were made to get the total wall surface as an output: File: wavosimulinksfun_mod.m line 352 added: Global Building Changes to the output solar heat released in zone The following changes were made to get the solar heat released in the zone as an output: File: wavosimulinksfun_mod.m line 352 added: Global Varu File: Wavovaru0606_mod.m line92 added: Varu.figainsolar = Building.Iow*(Ezon0.*(1-Facr')); Changes to the output solar heat on horizontal outdoor surface The following changes were made to get the solar heat on a horizontal outdoor surface as an output: File: wavosimulinksfun_mod.m line 352 added: Global Varu File: Wavovaru0606_mod.m line 19 [Esol, Lrad] replaced by [Esol, Lrad, E_hor_e] line 24 added: Varu.E_horizontal=E_hor_e line 27 added: Varu.E_hor_e=Varu.E_horizontal(uur,:); File: Zonfunf2_mod.m line 1 [Esol, Lrad] replaced by [Esol, Lrad, E_hor_e] line 59 added: E_hor_e = zeros(24,1); line 147 added: E_hor_e(uur,:) = Ehor(:)'; Changes to configuration of in- and output structure The changes to realize to modify the in- and output take only effect in the Simulink model of Hambase if changes are made to the file wavosimulinksfun.m. The changes to this file are described below. File: wavosimulinksfun_mod.m line 82 'Elements',['[1:' num2str(zonetot) ']'] replaced by 'Elements',['[1:' num2str(1) ']'] line 83 added: set_param([gcs '/Selector5'],'Elements',[num2str(1) '+[1:' num2str(zonetot) ']'],'InputPortWidth',num2str(5*zonetot+3)); line 84 'Elements',[num2str(zonetot) '+[1:' num2str(zonetot) ']'] replaced by 'Elements',[num2str(zonetot+1) '+[1:' num2str(zonetot) ']'] line 85 'Elements',[num2str(2*zonetot) '+[1:' num2str(zonetot) ']'] replaced by 'Elements',[num2str(2*zonetot+1) '+[1:' num2str(zonetot) ']'] Annex page 23

125 line 86 line 87 line 88 line 89 line line 92 line 100 line 101 line 377 'Elements',num2str(3*zonetot+1) replaced by 'Elements',num2str(3*zonetot+2) 'Elements',num2str(3*zonetot+2) replaced by 'Elements',num2str(3*zonetot+3) added: set_param([gcs '/Selector6'],'Elements',[num2str(3*zonetot+3) '+[1:' num2str(zonetot) ']'],'InputPortWidth',num2str(5*zonetot+3)); added: set_param([gcs '/Selector7'],'Elements',[num2str(4*zonetot+3) '+[1:' num2str(zonetot) ']'],'InputPortWidth',num2str(5*zonetot+3)); InputPortWidth', num2str(3*zonetot+2)) replaced by InputPortWidth', num2str(5*zonetot+3)) added: set_param([gcs '/Mux3'],'Inputs',num2str(zonetot)) 3*zonetot+2 replaced by 5*zonetot+3 2*zonetot replaced by 3*zonetot [Tcom ;Ta; Rva; Te; RVe] replaced by [Varu.E_hor_e; Tw; Ta; Rva; Te; RVe; Building.Atot'; Varu.figainsolar]; Modified version of HamBase The changes made to the Hambase files resulted in the modified version of Hambase as presented in figure D.2. The in- and output of this modified version is presented in table D.3 and its parameters in table D.4. Figure D.2: Simulink model of modified version of HamBase Annex page 24

126 Input Output Symbol Description Unit Symbol Description Unit Φ in_i Φ in_ii heat flow of system I released W q solar_e solar radiation on horizontal W/ m 2 in zone outdoor surface T wall mean wall temperature C heat flow of system II W T air_i indoor air temperature C released in zone RH i indoor relative humidity - G plant vapour flow released in zone kg/ s T e outdoor temperature C RH e outdoor relative humidity - A wall total wall surface m 2 Φ solar_i solar heat released in zone W Table D.3: In and output of modified version of Hambase Parameters Symbol Description Unit Calculation period - start year - - start month - - start day - - number of days to be simulated - The building Zones & volumes depth the depth of a zone m width the width of a zone m height the height of a zone m Construction components data R i internal heat transfer resistance m 2 K/ W d n material layer thickness m mat n material ID-number - R e heat transfer resistance at the opposite site m 2 K/ W a b external solar radiation absorption coefficient - e b external long wave emissivity - Glazing systems data U glas U-value without sun blinds W/ m 2 K CF r convection factor without blinds - ZTA solar gain factor without blinds - ZTA w solar gain factor with blinds - CF rw convection factor with blinds - U glasw U-value with blinds W/ m 2 K Orientations tilt azimuth External walls Annex page 25

127 zonenr select zone number from ZONES section - surf total surface area, including windows surface area m 2 conid select construction ID-number from CONSTRUCTION section - orid select orientation ID-number from ORIENTATIONS section - Windows in external walls exid select external construction ID-number from EXTERNAL WALLS section - surf surface are of the glazing m 2 glaid select glass ID-number from GLAZING section - Constant temperature walls zonenr select zone number from ZONES section - surf total surface area m 2 conid select construction ID-number from CONSTRUCTION section - temp constant temperature C Adiabatic temperature walls zonenr select zone number from ZONES section - surf total surface area m 2 conid select construction ID-number from CONSTRUCTION section - Profiles Ers irradiance level for sun blinds W/ m 2 dayper the starting time of a new period h Vinf the infiltration rate ACH Qint internal heat gains W Gint moisture gains kg/ s Profiles of the building - select a profile for each day of the week - Heating, cooling CF h convection factor of the heating system - CF had convection factor of the additional heating system - CF int convection factor of the casual gains - fbv moisture storage factor - CF fbi convection factor for the solar radiation due to furnishings - Table D.4: Parameters of Hambase Annex page 26

128 Annex E Modelling Concrete Core Conditioning Annex page 27

129 28

130 The realization of a simulation model of a Concrete Core Conditioning system requires a mathematical model that represents the heat transfer processes within the Concrete Core Conditioning system. This appendix starts with the description of this mathematic model that consists of sets of Ordinary Differential Equations and their constant parameters for the thermal resistances (R) and capacitances (C). Successively, the appendix describes how the mathematic model is implemented in Matlab and Simulink to result in the Concrete Core Conditioning simulation model that is suitable for all types of floors: intermediate floors, ground floors and roofs. Mathematic model CCC in an intermediate floor The mathematic model of the Concrete Core Conditioning system consists of a set of Ordinary Differential Equations. Based on figure 3.6 ( 3.1.2) the following Ordinary Differential Equations were formulated: = 4 [8] = [9] = [10] = ] [11] = [12] = [13] = ] [14] where: : thermal capacitance [J/ K] ] : solar heat released in zone [W/ m 2 ] : thermal resistance [K/ W] : convective heat transfer resistance [K/ W] : radiant heat transfer resistance [K/ W] : thermal resistance between pipe and [K/ W] centre construction layer : time [s] : temperature [ C] : construction temperature [ C] ] : surface temperature of construction layer [ C] : water inlet temperature [ C] : water outlet temperature [ C] with the indices : ceiling side of construction : floor side of construction Annex page 29

131 : indoor condition : water ( : number of room or construction layer 0 : number of construction layer The following relationships are used to calculate the thermal capacitances (C): = [15] = [16] = [17] = [18] = [19] = [20] = [21] where: : specific heat [J/ kg K] : density [kg/ m 3 ] : volume of construction layer [m 3 ] The following relationships are used to calculate the thermal resistances (R): = h [22] = = h h [23] [24] = = h h [25] [26] = h [27] = h [28] = h [29] Annex page 30

132 = h [30] where: : thickness of layer [m 2 ] : thermal conductivity [W/ m K] : convective heat transfer coefficient [W/ m 2 K] : radiant heat transfer coefficient [W/ m 2 K] The following mathematical relationship is used for the resistance R x [Koschenz et al., 2000]: = h 5 { δ 6 ( [ [31] where: : outside pipe diameter [m] : pipe spacing [m] : thermal conductivity of construction layer with CCC [W/ m K] A : surface area of construction [m 2 ] D c21/23 : thickness of lower/ upper part of construction [m] CCC in ground floors and roofs In comparison with an intermediate floor a ground floor or roof has other surroundings. As the surroundings are part of the RC-networks, it means that every type of floor construction will have its own RC-network as representation of the Concrete Core Conditioning system. These RC-networks are presented in figure 3.10 ( 3.1.2) and on basis of this figure it can be concluded that the changes due to the other surroundings are restricted to the Ordinary Differential Equations of temperature nodes T 1 and T 4. In case of the application of CCC in a ground floor or roof, instead of an intermediate floor, the following changes have to be made to the DE s: Ordinary Differential Equation of T 4 in case of CCC in a ground floor = ] [32] Ordinary Differential Equation of T 1 in case of CCC in a roof = ] [33] with the following indices: : outdoor condition : ground condition The ODE s introduce the thermal resistances R e_ground and R e_roof that are calculated with the following relationships: = h [34] = h [35] Annex page 31

133 where: : heat transfer coefficient [W/ m 2 K] The simulation model Implementation of the mathematic model in Matlab The mathematic model was implemented in Matlab with the use of an S-function. Within this S-function the Ordinary Differential Equations and the relationships to calculate the thermal capacitances (C) and resistances (R) were inserted. The S-function was also given a functionality to select the correct set of ODE s on basis of the given type of floor construction. The simulation model of the Concrete Core Conditioning system is one of the subsystems of a complete simulation model (figure 3.1 of 3). For the functionality of the complete model and to realize an in- and output structure that fits with the other subsystems, additional calculations were added to the S-function. The additional calculations that were added to the S-function are: Calculation of the mean radiant temperature The mean radiant temperature is based on the temperature of both the walls and ceilings and their surfaces areas. The following relationship is used to calculate the mean radiant temperature: = h h h h h h [36] The calculation of the heating and cooling power of the CCC construction The heat flow from the construction to the surrounding zone is used as an input of the building model. Furthermore, the water sided power of the CCC construction is required to determine the energy consumption. The following relationships are used: Heating power of floor side of construction }= } } } [W] [37] Heating power of ceiling side of construction = } } } [W] [38] Water sided heating power of CCC construction } = 4 [W] [39] where: 4 : water mass flow [W/ m 2 K] Note: Heat transfer coefficients within S-function The Heat Transfer Coefficients (HTC) are used to calculate the thermal capacitance (C). Based on literature ( 2.1.2) there has been chosen not to use constant values for the Heat Transfer Coefficients, but to calculate them on basis of the surrounding conditions. For practical reasons it was decided not to insert this calculation into the S-function of the Concrete Core Conditioning system, but to add an extra subsystem to the complete simulation model. Therefore, the heat transfer coefficients are treated as an input of the Concrete Core Conditioning system. Annex page 32

134 The complete S-function of the Concrete Core Conditioning system is inserted in appendix I. The simulation model in Simulink The S-function was inserted in Simulink where it was connected to its in- and output and this resulted in the simulation model of the Concrete Core Conditioning system as presented in figure E.1. The in- and output of this simulation model is presented in table E.1 and its parameters in table E.2. Figure E.1: Simulink model of Concrete Core Conditioning system Annex page 33

135 Input Output Symbol Description Unit Symbol Description Unit A wall surface area of the walls m 2 A floor/ceiling surface area of floor/ ceiling m 2 h rad_ce_i h rad_fl_i h cv_ce_i h cv_fl_i radiant heat transfer coefficient for ceiling side of construction W/ m 2 K Φ ccc_ceiling heating power of ceiling side of construction W radiant heat transfer W/ m 2 K Φ ccc_floor heating power of floor side of W coefficient for floor side of construction construction convective heat transfer W/ m 2 K Φ ccc_total heating power as sum of W coefficient for ceiling side of ceiling and floor side of construction construction convective heat transfer W/ m 2 K Φ ccc_water water sided heating power of W coefficient for floor side of CCC system construction water mass flow kg/ s T c2 construction temperature at C centre of layer 2 Φ solar_i solar heat released in zone W T c12 construction temperature at boundary layer 1-2 C q solar_e solar radiation on horizontal W/ m 2 T c23 construction temperature at C outdoor surface boundary layer 2-3 T air_i indoor air temperature C T c34 construction temperature at C boundary layer 3-4 T e outdoor temperature C T cs1 surface temperature of construction of layer 1 floor side C T e_ground outdoor temperature at C T cs1_rf surface temperature of C ground side construction layer 1 roof side T wall mean wall temperature C T cs4 surface temperature of C construction layer 4 ceiling side T w_in T w_in_gf T w_in_rf water inlet temperature for intermediate floor C T cs4_rf surface temperature of construction layer 4 ground floor side C water inlet temperature for C T w_out water outlet temperature for C ground floor intermediate floor water inlet temperature for C T w_out_rf water outlet temperature for a C roof roof T w_out_gf water outlet temperature for a C ground floor T mrt mean radiant temperature C Table E.1: In and output of Concrete Core Conditioning system Annex page 34

136 Parameters Symbol Description Unit General - number of zones to be calculated - - specification of the zones that have a ground floor or roof - Geometry depth the depth of a zone m width the width of a zone m Material specification density kg/ m 3 thermal conductivity W/ m K thermal conductivity of construction layer with CCC W/ m K specific heat J/ kg K Construction components - select the type of material used for each layer of every - floor (intermediate floor, ground floor or roof) D c thickness of each layer m Concrete Core Conditioning properties outside pipe diameter pipe spacing m m Heat Transfer Coefficients for ground floor and roof h e_ground heat transfer coefficient at ground side of ground floor (standard: 25 W/m 2 K (rad+cv)) W/ m 2 K h e_roof heat transfer coefficient at roof side of roof (standard: 25 W/m 2 K (rad+cv)) W/ m 2 K Table E.2: Parameters of Concrete Core Conditioning system Verification The model was verified with a static verification which is a method that compares the results of simulations and handmade calculations that are both performed with the same fixed input values. To perform the handmade calculations relationships are used that are based on the RC-network of the model (figure 3.10 of 3.1.2). The simulation model of the Concrete Core Conditioning system can be applied for 3 different types of floors, namely an intermediate floor, ground floor and roof. Therefore, the verification was performed for every floor type. Table E.3, E.4 and E.5 presents an overview of the handmade calculations, the fixed input values and the results. The simulation models used for this verification are enclosed in the digital appendix and named: CCC_basis_veri_grond.mdl (verification model for ground floor); CCC_basis_veri_inter.mdl (verification model for intermediate floor); CCC_basis_veri_roof.mdl (verification model for roof). Annex page 35

137 Static verification - Concrete Core Conditioning system (intermediate floor) Starting points Results handmade calculations Input Parameters Calculated parameters Calculated output Simulation results Output h rad_f l_i 4,7 width 7,2 C w T mrt 21,68 T mrt 21,68 h rad_ce_i 4,7 depth 5,4 C T cs1_rf T cs1_rf h cv _f l_i 3,3 D c1 0,008 C T cs1 22,96 T cs1 22,96 h cv _ce_i 1 ρ Dc C T c2 23,09 T c2 23,09 Φ solar_i 2100 λ Dc1 0,17 C T c12 23,02 T c12 23,02 q solar_e 600 C Dc C T c23 23,26 T c23 23,26 T e D c2 0,2 C T c34 23,34 T c34 23,34 T wall 20 ρ Dc R rad_f l_i 0, T cs4 23,35 T cs4 23,35 T air_i 20 λ Dc2 1,9 R rad_ce_i 0, T cs4_gf T cs4_gf T e_ground C Dc R cv _f l_i 0, Φ ccc_ceiling 435,23 Φ ccc_ceiling 435,23 T w_in 23 D c3 0,05 R cv _ce_i 0, Φ ccc_f loor 611,97 Φ ccc_f loor 611,97 T w_in_gf ρ Dc R 1 0, Φ ccc_total 1047,20 Φ ccc_total 1047,20 T w_in_rf λ Dc3 1,9 R 21 0, Φ ccc_water -72,80 Φ ccc_water -72,80 A wall 68,04 C Dc R 23 0, A f loor/ceiling 38,88 A f loor/ceiling 38,88 m dotw 0,28 D c4 0,05 R 3 0, T w_out 23,06 T w_out 23,06 ρ Dc R 4 0, T w_out_rf T w_out_rf λ Dc4 1,9 R x 0, T w_out_gf T w_out_gf C Dc Roof ρ w 1000 R e_ground 0, C w 4180 Ground floor d x 0,15 R e_ground 0, δ 0,0155 h e_ground 25 h e_roof 25 1) Starting points of handmade calculation The floor of a zone along a roof is an intermediate floor, therefore, these values (of intermediate floor) are required to perform the calculations. Handmade calculations Starting points Use of following simulation results T cs1 T cs1_rf T cs4 T cs4_gf 22,95541 C C 23,35046 C C Calculation of resistances 1. sum of resistance between T c2 and T cs1 0, K/ W 2. sum of resistance between T c2 and T cs4 0, K/ W 3. sum of parallel resistances T c2 and T cs1 & T c2 and T cs4 0, K/ W 4. sum of parallel resistances (3) and R x 0,00168 K/ W Calculation of heat flows and output temperatures for intermediate floor 5. mean radiant temperature 21,68 C 6. heat flow from T cs1 to zone 611,97 W 7. solar heat falling on floor 560,00 W 8. heat flow from T c2 to T cs1 51,97 W 8. heat flow from T cs4 to zone 435,23 W 9. solar heat falling on ceiling 560,00 W 10. heat flow from T c2 to T cs4-124,77 W 11. heat flow from T w_out to T c2-72,80 W 12. T c12 23,02 C 13. T c2 23,09 C 14. T c23 23,26 C 15. T c34 23,34 C 16. T w_out 23,06 C Calculation of additional output 17. Φ ccc_ceiling 435,23 W 18. Φ ccc_f loor 611,97 W 19. Φ ccc_total 1047,20 W 20. Φ ccc_water -72,80 W 21. A f loor/ceiling 38,88 m² Table E.3: Static verification of Concrete Core Conditioning Annex page system 36 in an intermediate floor

138 Static verification - Concrete Core Conditioning system (roof) Starting points Results handmade calculations Simulation results Input Parameters Calculated parameters Calculated output Output h rad_f l_i 4,7 width 7,2 C w T mrt 22,78 T mrt 22,78 h rad_ce_i 4,7 depth 5,4 C T cs1_rf 43,29 T cs1_rf 43,29 h cv _f l_i 3,3 D c1 0,008 C 12 1) T cs1 22,96 T cs1 22,96 h cv _ce_i 1 ρ Dc C T c2 29,05 T c2 29,05 Φ solar_i 2100 λ Dc1 0,17 C T c12 36,57 T c12 36,57 q solar_e 600 C Dc C T c23 28,26 T c23 28,26 T e 25 D c2 0,2 C T c34 27,86 T c34 27,86 T wall 20 ρ Dc R rad_f l_i 0, T cs4 27,46 T cs4 27,46 T air_i 20 λ Dc2 1,9 R rad_ce_i 0, T cs4_gf T cs4_gf T e_ground C Dc R cv _f l_i 0, Φ ccc_ceiling 1146,15 Φ ccc_ceiling 1146,15 T w_in 23 D c3 0,05 R cv _ce_i 0, Φ ccc_f loor 411,59 Φ ccc_f loor 411,59 T w_in_gf ρ Dc R 1 0, Φ ccc_total 1557,74 Φ ccc_total 1557,74 T w_in_rf 23 λ Dc3 1,9 R 21 0, Φ ccc_water -5474,72 Φ ccc_water -5474,72 A wall 68,04 C Dc R 23 0, A f loor/ceiling 38,88 A f loor/ceiling 38,88 m dotw 0,28 D c4 0,05 R 3 1) 0, T w_out 23,06 T w_out 23,06 ρ Dc R 4 0, T w_out_rf 27,24 T w_out_rf 27,24 λ Dc4 1,9 R x 0, T w_out_gf T w_out_gf C Dc Roof ρ w 1000 R e_ground 0, C w 4180 Ground floor d x 0,15 R e_ground 0, δ 0,0155 h e_ground 25 h e_roof 25 1) Starting points of handmade calculation The floor of a zone along a roof is an intermediate floor, therefore, these values (of intermediate floor) are required to perform the calculations, but they are a copy from the static verification of the intermediate floor. Handmade calculations Starting points Use of following simulation results T cs1 (surface temperature of floor side of intermediate floor) T cs1_rf T cs4 T cs4_gf 22,95541 C 43,29 C 27,46249 C C Calculation of resistances 1. sum of resistance between T c2 and T cs1_rf 0, K/ W 2. sum of resistance between T c2 and T cs4 0, K/ W 3. sum of parallel resistances T c2 and T cs1_rf & T c2 and T cs4 0, K/ W 4. sum of parallel resistances (3) and R x 0,00168 K/ W Calculation of heat flows and output temperatures for roof construction 5. mean radiant temperature 22,78 C 6. heat flow from T cs1_rf to outdoor 17775,16 W 7. solar heat falling on roof 23328,00 W 8. heat flow from T c2 to T cs1_rf -5552,84 W 8. heat flow from T cs4 to zone 1146,15 W 9. solar heat falling on ceiling 560,00 W 10. heat flow from T c2 to T cs4 586,15 W 11. heat flow from T w_out to T c2-4966,69 W 12. T c12 36,57 C 13. T c2 29,05 C 14. T c23 28,26 C 15. T c34 27,86 C 16. T w_out_rf 27,24 C Calculation of additional output 17. Φ ccc_ceiling 1146,15 W 18. Φ ccc_f loor 411,59 W 19. Φ ccc_total 1557,74 W 20. Φ ccc_water -5474,72 W 21. A f loor/ceiling 38,88 m² Table E.4: Static verification of Concrete Core Conditioning system in a roof Annex page 37

139 Static verification - Concrete Core Conditioning system (ground floor) Starting points Results handmade calculations Simulation results Input Parameters Calculated parameters Calculated output Output h rad_f l_i 4,7 width 7,2 C w T mrt 21,15 T mrt 21,15 h rad_ce_i 4,7 depth 5,4 C T cs1_rf T cs1_rf h cv _f l_i 3,3 D c1 0,008 C T cs1 20,97 T cs1 20,97 h cv _ce_i 1 ρ Dc C T c2 19,77 T c2 19,77 Φ solar_i 2100 λ Dc1 0,17 C T c12 20,40 T c12 20,40 q solar_e 600 C Dc C T c23 15,54 T c23 15,54 T e D c2 0,2 C T c34 13,42 T c34 13,21 T wall 20 ρ Dc R rad_f l_i 1) 0, T cs4 23,35 T cs4 23,35 T air_i 20 λ Dc2 1,9 R rad_ce_i 0, T cs4_gf 13,21 T cs4_gf 13,21 T e_ground 10 C Dc R cv _f l_i 0, Φ ccc_ceiling 532,01 Φ ccc_ceiling 532,01 T w_in 23 D c3 0,05 R cv _ce_i 0, Φ ccc_f loor 91,02 Φ ccc_f loor 91,02 T w_in_gf 23 ρ Dc R 1 0, Φ ccc_total 623,03 Φ ccc_total 623,03 T w_in_rf λ Dc3 1,9 R 21 0, Φ ccc_water 1969,64 Φ ccc_water 1969,64 A wall 68,04 C Dc R 23 0, A f loor/ceiling 38,88 A f loor/ceiling 38,88 m dotw 0,28 D c4 0,05 R 3 1) 0, T w_out 23,06 T w_out 23,06 ρ Dc R 4 0, T w_out_rf T w_out_rf λ Dc4 1,9 R x 0, T w_out_gf 20,73 T w_out_gf 20,73 C Dc Roof ρ w 1000 R e_ground 0, C w 4180 Ground floor d x 0,15 R e_ground 0, δ 0,0155 h e_ground 25 h e_roof 25 1) Starting points of handmade calculation The floor of a zone along a roof is an intermediate floor, therefore, these values (of intermediate floor) are required to perform the calculations, but they are a copy from the static verification of the intermediate floor. Handmade calculations Starting points Use of following simulation results T cs1 T cs1_rf T cs4 (surface temperature of ceiling side of intermediate floor) T cs4_gf 20,96942 C C 23,35046 C 13,21336 C Calculation of resistances 1. sum of resistance between T c2 and T cs1_rf 0, K/ W 2. sum of resistance between T c2 and T cs4 0, K/ W 3. sum of parallel resistances T c2 and T cs1_rf & T c2 and T cs4 0, K/ W 4. sum of parallel resistances (3) and R x 0,00168 K/ W Calculation of heat flows and output temperatures for roof construction 5. mean radiant temperature 21,15 C 6. heat flow from T cs1 to zone 91,02 W 7. solar heat falling on floor 560,00 W 8. heat flow from T c2 to T cs1-468,98 W 8. heat flow from T cs4_gf to ground 3123,39 W 9. solar heat falling on ground site of construction 0,00 W 10. heat flow from T c2 to T cs4_gf 3123,39 W 11. heat flow from T w_out to T c2 2654,41 W 12. T c12 20,40 C 13. T c2 19,77 C 14. T c23 15,54 C 15. T c34 13,42 C 16. T w_out_gf 20,73 C Calculation of additional output 17. Φ ccc_ceiling 532,01 W 18. Φ ccc_f loor 91,02 W 19. Φ ccc_total 623,03 W 20. Φ ccc_water 1969,64 W 21. A f loor/ceiling 38,88 m² Table E.5: Static verification of Concrete Core Conditioning system in a ground floor Annex page 38

140 Annex F Modelling HVAC system Annex page 39

141 Annex page 40

142 This appendix describes the relationships used for the mathematic model of the HVAC system, its implementation in Simulink and its verification. Mathematic model The relationships of the mathematic model are based on the information as described in Heating coil Because the absolute humidity isn t affected by the heating process the following relationship counts for the absolute humidity of the supply air after the heating coil: ) = ) [40] where: ) : absolute humidity of supply air after heating coil [kg/ kg] ) : absolute humidity of outdoor air [kg/ kg] The heating power of the AHU to condition the outdoor air to the desired supply air temperature can be calculated with: = 4 ] > [41] where: : heating power of AHU to heat supply air [W] 4 } : supply air volume [m 3 / h] : density of air [kg/ m 3 ] : specific heat of air [J/ kg K] ] > : supply air temperature [ C] : outdoor air temperature [ C] Cooling coil In contrast with the heating coil water vapour in the supply air can condensate on the cooling coil if it is cooled to the desired supply air temperature. This condensation takes only place if the partial pressure of water vapour in the supply air is higher than the water vapour saturation pressure on the surface of the cooling coil. So, condensation of the supply air takes place if: ] [42] where: : partial pressure of water vapour of outdoor air [Pa] ] : water vapour saturation pressure on cooling coil surface [Pa] The partial pressure of water vapour of the outdoor air can be calculated on basis of the relative humidity using the following relationships: = 2 8 = ] [43] Annex page 41

143 ] = ) ) 5 [ [44] where: : relative humidity of outdoor air [ - ] : outdoor air temperature [ C] The water vapour saturation pressure on the surface of the cooling coil can be calculated with: ] = ) [45] where: : mean surface temperature of cooling coil [Pa] Relationships to calculate the absolute humidity and cooling power The occurrence of condensation on the surface of the cooling coil determines the relationships used for the absolute humidity of the supply air after the cooling coil. Therefore, the following relationships counts for the absolute humidity of the supply air after the cooling coil: If no condensation takes place ] the following counts: ) = ) [46] If condensation takes place ] the following counts: ) = ) ) ) [47] where: ) : absolute humidity on surface cooling coil [kg/ kg] : mixing rate between outdoor air conditions [ - ] and conditions on the surface of the cooling coil The required absolute humidity s can be calculated with: Absolute humidity on the cooling coil surface: 2 ) = ( ( 2 [48] Absolute humidity of the outdoor air: 2 ) = ( ( 2 [49] where: : total outdoor air pressure (= Pa) [Pa] The mixing rate between the conditions of the outdoor air and the conditions on the surface on the cooling coil can be calculated with the following relationship (see figure F.1 for visualisation): Annex page 42

144 = 2 [50] where: : mean surface temperature of cooling coil [ C] ] > : supply air temperature [ C] Figure F.1: Visualisation of mixing rate m cc. The point m cc is located on the line between the outdoor temperature T e and the average surface temperature of the cooling coil T ahu_cc_mean. The temperature of the supply air determines the exact position of m cc on this line. For the calculation of the cooling power of the AHU that is required to condition the outside air to the desired supply air temperature the occurrence of condensation on the cooling coil should be taken into account too. Therefore, the following relationship of the cooling power distinguishes a sensible and latent part: = [51] where: : cooling power of AHU to cool supply air [W] : sensible part of cooling power of AHU [W] : latent part of cooling power of AHU [W] The sensible part of the cooling power can be calculated with: = 4 ] > [52] Just like with the calculation of the absolute humidity of the supply air after the cooling coil, the calculation of the latent part of the cooling power also depends if condensation on the cooling coil takes place. Therefore the following relationships count: If no condensation takes place ] the following counts: = [53] Annex page 43

145 If condensation takes place ] the following counts: where: = 4 ) 2 ) 5 [54] } : specific latent heat of vaporization [J/ kg] ) : absolute humidity of supply air after cooling coil [kg/ kg] Relationships to calculate the local heating and cooling power The supply air exchanges heat with the air in the zones. This local heating or cooling power of the supply air can be calculated with: } = 4 ] > [55] where: } : local heating cooling power of supply air [W] : indoor air temperature [ C] The simulation model The mathematic model of the HVAC system was implemented in Simulink with the use of several Simulink blocks. These blocks were integrated into 1 subsystem which makes an easy connection to the in- and output of the HVAC system possible. Within this subsystem also the following functions were integrated: The control strategy of the supply air temperature on basis of the outdoor temperature. This strategy can be given on basis of two points as presented in figure F.2; The operation time of the Air Handling Unit that can be defined with the start and stop time. The Simulink model of the HVAC system is presented in figure F.3. The in- and output of this simulation model is presented in table F.1 and its parameters in table F.2. Supply air temperature [ C] Tsa2 Tsa1 Te1 Te Outside temperature [ C] Figure F.2: Control strategy of the supply air temperature. This control strategy is defined with the points Te1, Te2, Tsa1 and Tsa2 and can be given as parameter of the HVAC system. Annex page 44