putational domain contained 8 blocks surrounding the central one. All 9 blocks had the same arrangement. Each block comprised a total of 72 residentia

Transcription

1 The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, 2012 Ventilation efficiency indices for evaluating ventilation performance of newly-built urban area Tingting Hu a, Ryuichiro Yoshie b a Tokyo Polytechnic University, Kanagawa, Japan, tingting@arch.t-kougei.ac.jp b Tokyo Polytechnic University, Kanagawa, Japan, yoshie@arch.t-kougei.ac.jp ABSTRACT: This paper aims to numerically investigate relationship among ventilation indices which were adopted for estimating ventilation efficiency in newly-built residential areas at pedestrian level. A reference urban block model was designed according to a typical residential area in Shanghai. Urban parameters including building coverage ratio, passage width, building array and building height variation were considered. The ventilation efficiency was evaluated by spatial averaged wind speed ratio ( ), volume-averaged normalized concentration (C * ), and visitation frequency (). The results showed that, for most cases, a general relationship was found among the three indices: a large value of and a low value of resulted in a low value of C *. However, a few exceptions were found in the densest case and these were explained by flow rate analysis. KEYWORDS: urban ventilation; ventilation indices; CFD. 1 INTRODUCTION Recently, urban ventilation performance is becoming an important concern because of urban heat island effects and air pollution. It is necessary to evaluate urban ventilation performance based on different design parameters in order to improve planning of new-built areas. Volume-averaged wind speed ratio ( ) (Ng, 2009), volume-averaged normalized concentration (C*),purging flow rate (PFR), residence time (TP) (Kato et al, 2003) and visitation frequency () (Bady et al, 2008), have been successfully applied for evaluating ventilation performance in urban area. The authors have also used the above indices to investigate urban ventilation performance in newly-built area by numerical simulation (Hu and Yoshie, 2011). Based on this previous studies, C* reflected the integrated effects of other indices such as and, so it can be served as the core index for evaluating ventilation performance. Generally, large values and small values resulted in low C* values. However, some exceptions were found, for example, low C* values were found with low values or large values. The reason of such discrepancy needs to be investigated in detail. Therefore, flow rate and mass of pollutant passing through each surface of target control volume were investigated and analyzed. A fulllength paper should have a short introduction. This should state the reasons for the work, with brief reference to previous work on the subject. 2 ANALYSIS OUTLINE 2.1 Analysis model A simplified urban block model (Fig. 1a) was designed according to a typical residential area in Shanghai (Fig. 1b). Figure 1c showed an enlarged view of a center block in Figure 1a. The com- 1629

2 putational domain contained 8 blocks surrounding the central one. All 9 blocks had the same arrangement. Each block comprised a total of 72 residential buildings (48m (L) 12m (W) 18m (H)) with 6 stories. The building coverage ratio (BCR), which represents the ratio of ground floor area to lot area, was 40% and the floor area ratio (FAR), which represents the ratio of total floor area to lot area, was 230%. To compare the ventilation efficiency of different urban patterns, other BCRs and arrays (Layouts 2-18) were considered, as shown in Table 1. The BCR was changed by increasing the building height while keeping the FAR constant. (The sum of building volumes was kept constant). The lengths and widths of buildings were not changed. The passage widths D 1 and D 2 between adjacent buildings (shown in Fig. 1f) changed with BCR and building array. The main road width in these models was 20m for all cases, as shown in Fig. 1a. The minimum distances from buildings to the main road side were designed according to the existing urban planning regulations in Shanghai. 2.2 Computational condition The CFD technique with the standard k- model was used. Three wind directions 0, 45 and 90, shown in Figure 1a, were analyzed. The computational domain contained 8 blocks surrounding the central one. All 9 blocks had the same arrangement. The domain size was 1378 m (x) 1378 m (y) 198 m (z) for the reference case. A structured grid of 2,337,984 meshes was made. Table 2 shows the calculation conditions (AIJ guideline). Table 1. Parameters for all layouts Layout H (m) BCR (%) FAR (%) Array Layout H (m) BCR (%) FAR (%) Array A & LH A & LH A & SH A & SH S & SH S & SH S A 8 12 & LH A 9 18 & LH A Note: A: Aligned array; S: Staggered array; LH: Low and High spaced array; SH: Staggered Height array Table 2. Calculation conditions Code Fluent 6.3 Turbulence model Standard k- model u U z / z, 0.27, z 10m, U 3 Inlet m/s ref ref ref ref 2 ( z) u( z), I ( z) 0.1 z / zg, zg I 550m k 1/ 2 d ( u( z)) Cu k ( z), Cu dz Outflow 0.09 Outlet Upper and side surface Symmetry (for wind direction 0, 90) surface and ground Wall function 1630

3 The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, 2012 (a) Reference urban block model (b) Typical residential area in Shanghai (Google map) (c) Layout 1 (BCR40%) (d) Layout 2 (BCR20%) (e) Layout 3 (BCR13%) (f) Layout 4 (BCR10%) (g) Layout 5 (BCR20%) (h) Layout 6 (BCR13%) (i) Layout 7 (BCR10%) (j) Layout 8 (BCR 40%) (k) Layout 9 (BCR 20%) (l) Layout 10 (BCR 13%) (m) Layout 11 (BCR 10%) (n) Layout 12 (BCR 40%) (o) Layout 13 (BCR 20%) (p) Layout 14 (BCR 13%) (q) Layout 15 (BCR 10%) 10&14 36m 72m 11&15 54m 90m H (m) Layout 8&12 9&13 12m 18m 24m 54m (r)layout 16 (BCR 20%) (s)layout 17 (BCR 30%) (t) Layout 18 (BCR 30%) H of non-uniform layout Figure 1. Analysis model 1631

4 Take layout 1 (BCR=40%, Aligned array) as an example: Pollutant Source Volume (PSV) Location:0-2m (z) volume of center block Size:326m (L B ) 326m (L B ) 2m (h) (Note: except building part) Five surfaces of PSV a. Front (Windward surface) b. Back (Leeward surface) c., Right (side surfaces) d. Top (upper surface) Figure 2. Pollutant Source Volume (PSV) Wind conditions at pedestrian level in an urban area play an important role in the dispersion of vehicle pollutants, diffusion of heat, and ventilation of buildings, as well as the comfort and safety of pedestrians. Therefore, it is necessary to understand the pedestrian wind environment around buildings 0-2m (z) and to take them into account in urban ventilation design. A uniform pollutant source assumed to be a passive scalar was generated throughout the pollutant source volume (PSV) (0-2m (z) volume of the center block), as shown in Figure 2, to simulate pollution from residence areas and vehicles. Six analysis indices were used to evaluate urban ventilation efficiency for all cases. 2.3 Analysis indices Spatial Wind Velocity Ratio ( ) Spatial wind velocity ratio ( ) is defined as the ratio of average wind velocity at pedestrian level to a reference wind velocity [Ng, 2009], and is calculated as: =U p /U ref (1) where U p is the volume-averaged wind speed in PSV (m/s) and U ref is the inflow wind velocity at 10m height (m/s) Volume-averaged Normalized Concentration (C * ) C * is defined as the volume-averaged normalized concentration, and is calculated as: C * =(C U ref W 2 )/Q (2) where C is the calculated volume-averaged concentration (kg/kg), Q is the pollution emission rate (m 3 /s) and W is the building width (m) Inflow rate of air (q air,in ) q air,in is the inflow rate of air passing through each surface of PSV, and is calculated as: air,in n i1 i in, i q Au (3) where is the air density (kg/m 3 ), A i is the inflow area of cell face i (m 2 ), u in,i is the timeaveraged normal inflow wind velocity of cell face i (m/s), and n is the cell number at boundary surface of PSV. 1632

5 The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, Inflow rate of pollutants (q P,in ) q P,in is the inflow rate of pollutants passing through each surface of PSV, and is calculated as: n P,in i i in, i i i in, i i1 q Ac u Acu (4) where c i is time-averaged pollutant concentration at the boundary of cell face i (kg/kg), c i is the concentration fluctuation (kg/kg), and u in,i is the inflow velocity fluctuation (m/s) Outflow rate of pollutants (q P,out ) q P,out is the outflow rate of pollutants passing through each surface of PSV, and is calculated as: n P,out i i out, i i i out, i i1 q Acu Acu (5) where uout,i is the time averaged normal outflow wind velocity of cell face i (m/s) and u out,i the outflow velocity fluctuation (m/s). is Visitation Frequency () represents the number of times a particle enters the domain and passes through it (Bady et al, 2008). To calculate, the following equation was applied: =1+q P,in /q p (6) where q P is the pollutant generation rate q P =PSV S, PSV is the Pollutant Source Volume (m 3 ), and S is the uniform generation source strength (kg/m 3 s). 3 RESULT AND DISCUSSION Based on previous studies (Hu and Yoshie, 2011), C* reflected the integrated effects of other indices such as and, so it can be served as the core index for evaluating ventilation performance. Generally, large values and small values resulted in low C* values. However, some exceptions were found, for example, low C* values were found with low values or large values. In order to investigate such discrepancy in detail, flow rate and mass of pollutant which reflected by inflow rate of air (q air,in ); inflow rate of pollutants (q P,in ) and outflow rate of pollutants (q P,out ) passing through each surface of target control volume were studied and analyzed. 3.1 Relationship between and C * All the cases were classified by three wind directions (Fig. 3a) and four BCRs (Fig. 3b). As expected, and C * were negatively correlated for most cases. Several exceptions were indicated by gray dotted circles in both figures. 1633

6 C * A LH wind direction C * A LH BCR= 40% 30% 20% 13% 10% (a) Classified by wind direction Figure 3. Relationship between and C * (b) Classified by BCR For =0, 45, C * decreased as increased except at three points with both high C * values and values, which were enclosed by the gray dotted circle. From Figure 3b, the three exceptions share the same BCR (40%) which were the densest situations. The three cases were A and LH arrays. Figures 4a and 4b showed the view of center block of those two arrays and Figure 4c showed that of SH array with BCR (40%) for reference. Uniform height (H=18m) Low High Low High (a) Aligned array (A) (b) Low and High spaced array (LH) (c) Staggered Height array (SH) C* array array array (d) (e) C* (f) Figure 4. Ventilation performance of Aligned array, LH array and SH array ( = 0, BCR = 40% ) As displayed in Figure 4d, values of A and LH array were higher than that of SH array. It was because in dense area, small passage width D 2 made the passage parallel to the wind direction like a pipe in the A and LH arrays. This pipe-like flow can speed up the windin stream-wise direction and cause large value of. Although values were different between A, LH and SH array, C * values were almost the same (Fig. 4e). Therefore, the discrepancy that large values and high C* values occurred for A and LH arrays. It can be interpreted by flow rate analysis depicted in Figure 5. According to Figure 5b, on one hand, an even larger amount air entered PSV via the front surfaceof the A and LH arrays, and much less air entered through the top surface than for the SH array. One the other hand, as displayed in Figure 5c, even larger amount pollutant was ex

7 The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, 2012 hausted PSV via the back surfaceof the A and LH arrays, and much less pollutant was exhausted through the top surface than for the SH array. These two reasons resulted in a large value of C *.It explained the apparent contradictions between the large and C * values. It is noted that the contributions of each surface were different in terms of outflow rate of pollutant(fig. 5c). For A and LH arrays, larger outflows of pollutant discharged from the back surface than for SH array. This was detrimental to downstream regions. Therefore, although C * was nearly the same in PSV for the three arrays, SH array was more favorable for downstream regions. q p,in 4x10 4 3x10 4 2x10 4 1x10 4 Top Front Back Right q air,in 4x10 3 3x10 3 2x10 3 1x10 3 Top Front Back Right q p,out 2.0x x x x10 4 Top Back Front Right 0 0 (a) Inflow rate of pollutants (b) Inflow rate of air (c) Outflow rate of pollutants Figure 5. Flow rate of Aligned array, LH array and SH array ( = 0, BCR = 40%) For =90, the relationship between and C * was not clear. was low and showed little difference while C * showed large variations for all the cases. 3.2 Relationship between and C * The relationship between and C * was classified by BCRs (Fig. 6a) and building arrays (Fig. 6b) respectively. It was shown that C * generally increased with the increase of. However, there were two exceptions C * BCR= 40% 30% 20% 13% 10% (a) Classified by BCR Figure 6. Relationship between and C * C * A S LH SH (b) Classified by building array One was large values of C * and small values of (pointed out by the gray dotted polygon). It is noted that most of those exceptions were for A and LH arrays with BCR=40% for =0, 90. For =0, as displayed in Figures 4e and 4f, for A and LH array, C * values were high while values were small. The explanation was given in Figure 5. According to Figure 5a, a small amount of pollutant re-entered PSV, resulting in a small value of for A and LH array. However, the amount of inflow air and outflow of pollutant to PSV were also small for those cases (Figs. 5b and 5c). Therefore, the pollutant couldn t be diluted and removed and led to a high val- 1635

8 ue of C *. For LH array in the case of =90 (Fig. 7b), C * values were high (Fig. 7e) while values were small (Fig. 7f). The reason was shown in Figure 8. A small amount of pollutant reentered PSV, lead to small value for LH array (Fig. 8a). Meanwhile, the outflow of pollutant (Fig. 8b) and amount of inflow air (Fig. 8c) to PSV were also small and caused large C * values. This explained the contradiction that small value and large C * value. Uniform height (H=18m) Low High Low High (a) Aligned array (A) (b) Low and High spaced array (LH) (c) Staggered Height array (SH) C* array array array (d) (e) C* (f) Figure 7. Ventilation performance of Aligned array, LH array and SH array ( = 90, BCR = 40% ) Another exception was the A array with BCR=40% for =90 (indicated by a black dotted circle in Fig. 6). As depicted in Figures 7e-7f, value was very large while the C * value was not so high. According to Figure 8a, a large amount of inflow pollutant re-entered PSV through the top surface, resulting in a large value of. However, the outflow of pollutant and inflow of air were also very large and promoted exhausting and diluting of pollutant (Figs. 8b and 8c). Thus, the value of C * was not so high q p,in 1.2x x x x x x Top Front Back Right q p,out 2.5x x x x x (a) Inflow rate of pollutants (b) Outflow rate of pollutants (c) Inflow rate of air Figure 8. Flow rate of Aligned array, LH array and SH array ( = 90, BCR = 40%) Top Back Front Right q air,in 6x10 3 5x10 3 4x10 3 3x10 3 2x10 3 1x Top Front Back Right 3.3 Relationship between and Figures 9a and 9b showed that and were negatively correlated. As displayed in Figure 9a, for =0, 45, decreased as increased, and for =90, correlation between and was not clear. was low and showed few changes while showed large differences among all the cases. The A array with BCR=40% for =90 showed the largest value of. As 1636

9 The Seventh International Colloquium on Bluff Body Aerodynamics and Applications (BBAA7) Shanghai, China; September 2-6, 2012 discussed in Figure 8a, the largest amount of pollutant re-entered PSV through the top surface, so the value of was largest for this case % wind direction % A S LH SH (a) Classified by wind direction Figure 9. Relationship between and (b) Classified by building array 4 CONCLUDING REMARKS In order to investigate the ventilation efficiency of newly-planned residential areas, CFD simulations were carried out for various building arrangements. A reference urban model was designed according to a typical existing residential area in Shanghai. Keeping FAR constant, other urban models were designed by changing urban parameters (building coverage ratio, passage width, building array and building height variation). The ventilation efficiency of the different cases were evaluated by spatially averaged, C *, and. The detailed ventilation information reflected by inflow rate of pollutants (q P,in ), outflow rate of pollutants (q P,out ) and inflow rate of air (q air,in ) were used to explain the relationship among three indices(, C *, and ). Relationships among ventilation indices (, C *, and ) were summarized for most cases. In general, large and small resulted in low C *. However, a few exceptions were found in the dentist cases (BCR=40%). They were explained by flow rate analysis. In detail, with the increase of value, C * and values decreased respectively for =0, 45 except for A and LH array with BCR=40%. And for =90, relationship between value and C *, values were not clear, was low and showed few changes while C * and showed large differences among all the cases. With the increase of value, C * value increased for all wind directions. 5 ACKNOWLEDGEMENTS This study was funded by the Ministry of Education, Culture, Sports, Science and Technology, Japan, through the Global Center of Excellence Program, , which is gratefully acknowledged. 1637

10 6 REFERENCES 1 Ng, E.,2009. Air ventilation assessment for high density city An experience from Hongkong, Proceedings of the seventh International Conference on Urban Climate. Yokohama. 2 Kato,S., Ito,K., Murakami,S., Analysis of visitation frequency through particle tracking method based on LES and model experiment. Indoor Air 13(2): Bady,M., Kato,S., Huang,H.,2008.Towards the application of indoor ventilation efficiency indices to evaluate the air quality of urban areas. and Environment 43: Hu, T., Yoshie,R., Effects of building arrangement on ventilation performance in newly-built urban area. Proceedings of The Thirteenth International conference on Wind Engineering (ICWE13), Amsterdam, The Netherlands. 5 Google Maps URL: 6 Tominaga,Y., Mochida,A., Yoshie,R., Kataoka,H., Nozu,T., Yoshikawa, M., Shirasawa,T.,2009. AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings, Journal of Wind Engineering and Industrial Aerodynamics 96,