Performance Improvement Analysis for a Negative-pressurized Biosafety Level Laboratory

Transcription

1 Performance Improvement Analysis for a Negative-pressurized Biosafety Level Laboratory F.J. Wang* and J.S. Huang 1 Department of Refrigeration, Air Conditioning and Energy Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan SUMMARY It is vital to provide negative-pressurized environment for infectious control and disease research in the biosafety level (BSL) laboratory. However, there is no official guideline of the layout arrangement for air distribution system in the negative-pressured environment. In this study, numerical simulation has been carried out at a BSL-3 laboratory in a district hospital to determine the better layout for contamination control. Computational fluid dynamics (CFD) simulation with three supply air arrangement alternatives has been conducted to investigate the airflow distribution as well laboratory. The results from revealed that the L-type arrangement for supply air diffusers will achieve better ventilation efficiency. Different arrangement of air distribution could be assessed extensively not only by airflow simulation but also by field measurement to achieve the infectious control purpose. The local mean age-of-air also identified the most satisfied ventilation performance due to small mean age-of-air which reveals better contamination control. It also indicated that the ventilation performance can be improved by arranging the supply air layout. It was also expected that CFD aided simulation could identify strategies for best practice at design stage as well as reduce running cost at full operation. INTRODUCTION Due to the World Health Organization still recognized tuberculosis (TB) as a major public health problem until now, global efforts to control TB have expanded extremely in most healthy care facilities and micro-bacteriology laboratories. Kim et al. (2007) reported that the risk of personnel for contracting TB in the laboratory was twice higher than that of non-laboratory workers. It is vital and essential to provide negative-pressurized environment for infectious control in the biosafety level (BSL) laboratory. Recent research on ventilation performance against airborne infection has been investigated thoroughly by Chow et al. (2005). They also investigated that surgical site infection due to airborne bacteria is a main concern in developing the HVAC system. Another extensive review on the air movement under infection control concern has been presented by Pereira et al. (2005). Their study also revealed the control strategies which could reduce the risks of contamination and the microbiological control for the air distribution system have been analysed extensively. Computational fluid dynamics (CFD) simulation is a widelyaccepted scientific technique that allows improvement of airflow distribution for cleanroom contamination control (Wang et al. 2009). Some alternative arrangements under a limited budget as well as reduced trial-and-error effort have been conducted extensively. Zao et al. (2004) used the CFD codes successfully to simulate the air distribution and contamination decay as well as comparison of indoor contamination concentration in different rooms. Besides, the biological contaminant control under different ventilation models in the hospital has been investigated by using CFD simulation (Zhang et al. 2008). Results revealed that improving air flow distribution could reduce particle deposition on critical surface successfully. Moreover, ventilation effectiveness in aircraft cabins was investigated extensively for minimizing the cross-contamination of passengers by conducting CFD simulation and full scale experiment (Wang et al. 2008). The results revealed that the local mean age of air was affected not only by air velocity, but also by the local airflow patterns such as recirculation. The concept of age-of-air, which was derived from temporal mixing theory, has been widely adopted to evaluate the ventilation performance (Sandberg et al. 1983). Federspiel (1999) investigated the development of methods for calculating air change effectiveness based on age-of-air measurement. Besides, the influence of a thermal boundary conditions on the air change efficiency of a mechanical ventilation system has been studied extensively (Tommso et al. 1999). Furthermore, the ventilation efficiency of different ventilation patterns arranged by two inlet and two outlet diffusers at different locations was investigated by Chung et al. (2001). By using the tracer-gas techniques to the experimental program, a concentration decay of CO 2 is used to calculate the ventilation efficiency and air change rate. The results indicate that the ventilation efficiency might be dominantly influenced by location of diffuser rather than air change rate. In this study, numerical simulation of a full-scale has been carried out at a TB laboratory in a district hospital to determine the better layout for contamination control. CFD simulation with three supply air arrangement alternatives were conducted to investigate the airflow distribution as well laboratory. The CFD simulation technique was applied to survey airflow characteristics based on field-testing data. Furthermore, the index of age-of-air was conducted to evaluate the ventilation performance under different supply air arrangement alternatives extensively. SYSTEM DESCRIPTION AND CFD SIMULATION The layout of the investigated biosafety level 3 (BSL-3) negative-pressurized TB laboratory is shown in Figure 1. The dimension of the BSL-3 lab is at length of 8.5 m, width of 7.0 m, and height of 2.4 m respectively. There is a main experimental table at the center of the lab with the dimensions of 2.6m 1.5m 0.8m (length width height). Some experimental equipments including 4 incubators, 2 centrifuges, 2 refrigerators (4 o C) and -80 o C freezer were sketched in the layout as well. There are 2 biosafety cabinets (BSC) with each airflow capacity of 995 m 3 /h. Some critical ISBN: COBEE2018-Paper255 page 764

2 4th International Conference On Building Energy, Environment areas including stained region, BSCs and centrigues were equipped with exhaust air duct and exhaust grilles above. The investigated lab with cleanliness level 100,000 (ISO class 8) with 12 air change per hour (ACH) specification. The other specified design conditions are: temperature 21±2 ( ), humidity 60±10 (%RH) and pressure difference Pa respectively for the main area within the lab. Due to the investigated lab was retrofitted from the exiting healthy care building, existing exhaust air grilles along with experiment equipments were constrained with few flexibility. The preliminary study through numerical simulation to evaluate the contamination control for critical area will focus on the alternative arrangement of supply air with high efficiency particulate air (HEPA) filters. The full scale geometric model for CFD simulation of the investigated lab is shown in Figure 2. Exhaust air (EA) plates and exhaust air grille s (EAG) along with returned air (RA) grilles were sketched as well. Three types of supply air (SA) with 5 HEPA filters arrangement alternatives including case (a) vertical, case (b) horizontal and case (c) L type arrangement have been conducted and compared extensively. A commercial CFD code, FLUENT, was used to simulate the velocity field and concentration distribution of the lab. The governing equations solved by FLUENT including the threedimensional time-dependent incompressible Navier-Stokes equation, time dependent convection diffusion equation and k-ε turbulence equations. The finite control volume method with a Semi Implicit Method for Linked Equations (SIMPLE) algorithm was employed to solve all the governing equations simultaneously. After solving the velocity distribution, the transient simulations of concentration distribution were implemented. The concentration decay method based on mass concentration equation could be derived accordingly. The temperature and face velocity of the HEPA filters were measured using a hot-wired anemometer as the boundary conditions for numerical simulation. Particle counts were conducted with a Met-One Model 3313 particle counter, sensitive to particles larger then 0.5μm. Table1 depicts the air flow rate measured for numerical simulation input of each HEPA, exhaust grille and BSC. Furthermore, the concentration decay simulation was employed by assuming the initial concentration of CO2 at 3000 ppm in the lab. Background CO2 concentration level was assumed to reach 350 ppm which corresponded to the CO2 concentration of ambient environment. The grid test for 517,922 cells and 770,570 cells possessed the relative error of 4.58 % while grid test for 770,570 cells and 960,904 cells presented the relative error of 1.42 %. It revealed that 770,570 grid cells were acceptable for CFD simulation in this study. SA2 SA3 SA4 SA5 BSC -995 EAG2 EAG3 EA1 EA2 EA3 ISBN: Layout of the investigated biosafety level 3 Figure 2. Geometric model of the BSL-3 laboratory (L-type arrangement) Figure 3. Schematic layout of the monitoring points at the height of 1.6m Table 1. Air flow rate for simulation Position SA1 Airflow rate 3 (m /hr) Position EAG1 Airflow rate 3 (m /hr) Figure 1. laboratory RESULTS AND DISCUSSION To evaluate the ventilation performance and to investigate the effect of different arrangement of supply air HEPA arrangement at the lab, some critical monitoring points (as shown in Figure 3) at the height of 1.6 m in front of BSC (point 1 and point 2) and in front of centrifuges were chosen (point 3 and point 4) due to potentially high risk for contamination. These points were chosen to survey the concentration decay rate at the critical area of the lab. Simulation results were performed by concentration decay transient simulation which was conducted by assuming the initial contamination concentration of CO2 at 3000 ppm and then dilute to the background concentration level at 350 ppm. COBEE2018-Paper255 page 765

3 Figure 4 depicted the transient simulation of concentration decay rate at specified monitoring points at the lab with 3 cases of supply air HEPA arrangement alternatives. Case A with vertival arrangement presents an acceptable performace for concentration decay for point 2, 3, 4, but slow decay for point 1 as it takes about 400 seconds to dilute the concentration to 350 ppm. Case B with horizontal arrangement represents similar trend for all mointoring points including point 4 which reveals better ventilatin performance then case A. It indicated that the concentration decreased faster for the case B with horizontal arrangement. The concentration decay curve for case (C) with L type arrangement demonstrated less time (about seconds) needed for all monitoring points to reach 350 ppm concentration level than previous cases which represented the better ventilation performance. This simulation results also revealed that the ventilation performance can be inproved just by relocating the supply air HEPA without any extra cost. To examine the improvement potential under different supply air arrangement cases, transient simulations at t=180 seconds with different depth (Y axis) in the lab were conducted as well. The velocity distribution and concentration profile are presented in Figure 5 for 3 cases. The concentration profiles at the depth of 3.75 m were also illustrated for 3 cases in Figure 5 (a) through transient simulation to examine the concentration decay at the lab. Case A demonstrates higher concentration about 2000 ppm at point 1 due to supply air HEPA blocked by the upper table above the main experimental table. The concentration level of monitoring point 2, 3, 4 is not so worse due to adjacent to exhaust air grille. The velocity distribution is presented for 3 cases in Figure 5 (b). Simulation trend corresponds to Figure 5(a) for air distribution under different arrangement cases. The airflow distribution extends outward obviously after leaving the supply air vents of HEPA filters in case A at point 1. It also presents obvious vortex velocity vector above the experiment table. These vortex vectors might cause turbulence of airflow and result in potential cross contamination. However, the vortex velocity vectors can be reduced apparently by re-arrange the supply air HEPA layout such as case B and case C. It also demonstrates that the strategy for contamination control by arranging the layout of supply air layout might be feasible. To assess and quantify the ventilation performance of the operation room, local mean age-of-air was calculated using the theoretical method (Sandberg et al. 1983). The concept of age-of-air based on numerical concentration level has been incorporated. Calculation of mean age-of-air gives the time elapsed and it can be used to characterize the airflow pattern and ventilation performance. Transient simulation for concentration field at arbitrary point is essential for calculation the age-of-air. Furthermore, the calculation of concentration decay after 600 seconds, room local mean age-of-air is shown for all monitoring points of 3 cases are shown in Figure 6. The local mean age-of-air at point 1 of case A reduced obviously by re-arrange the supply air HEPA arrangement. The local mean age-of-air exhibits the same trend with the previous concentration simulation. Case C presents the most satisfied ventilation performance due to small mean age-of-air which reveals better contamination control. It also indicated that the ventilation performance can be improved by arranging the supply air layout. Furthermore, the calculation of local mean age-of-air based on numerical simulation has been compared and analysed with field test data of particle counts. As depicted in Figure 7, the local mean age-of-air corresponds to the similar trend of particle counts for the case C at each monitoring point. (a) (b) (c) Case A Case B Case C Figure 4. Contamination control performance for different supply air arrangement ISBN: COBEE2018-Paper255 page 766

4 4th International Conference On Building Energy, Environment (a) Concentration contour Figure 7. Comparison of particle counts and local mean age of air CONCLUSIONS Nowadays, there is little official guideline about the layout arrangement for air distribution system in the negativepressured environment. In this study, numerical simulation of a full-scale BSL-3 laboratory has been carried out to determine the better layout for contamination control. CFD simulation with three supply air arrangement alternatives has been conducted to investigate the airflow distribution as well laboratory. Different arrangement of air distribution could be assessed extensively not only by airflow simulation but also by field measurement to achieve the contamination control concern. Ventilation performance could be achieved effortlessly with less expenditure through the proper arrangement of supply air HEPA. It is also expected that CFD aided simulation could identify strategies for best practice and achieve the contamination control purpose. (b) Velocity distribution ACKNOWLEDGEMENT Figure 5. Comparison of concentration and velocity distribution for different layout arrangement The authors would like to express their great appreciation to the financial support by the National Science Council under the grant No. MOST E CC3. REFERENCES Chung K. C. and Hsu S. P Effect of Ventilation Pattern on Room Air and Contaminant Distribution Building and Environment, Vol. 36, pp Chow T. T., and Yang X. Y Ventilation performance in the operating theatre against airborne infection: numerical study on an ultra-clean system Journal of Hospital Infection, Vol. 59, pp Kim S. J., Lee S. H., Kim I. S., Kim H. J., Kim S. K. and Rieder H. L Risk of occupational tuberculosis in National Tuberculosis Programme laboratories in Korea International Journal of Tuberculosis and Lung Disease, Vol. 11, pp Federspiel, C. C Air-change Effectiveness: Theory and Calculation Methods, Indoor Air, Vol. 9, pp Figure 6. Comparison of local mean age of air ISBN: Pereira M. L. and Tribess A A review of air distribution patterns in surgery rooms under infection control focus Thermal Engineering, Vol. 4, pp COBEE2018-Paper255 page 767

5 Sandberg M. and Sjöberg M The Use of Moments for Assessing Air Quality in Ventilated Rooms Building and Environment, Vol. 18, pp Tommso R., DI M. and Nino E Influence of the boundary thermal conditions on the air change efficiency indexes Indoor Air, Vol. 9, pp Wang A., Zhang Y., Sun Y. and Wang X Experimental Study of Ventilation Effectiveness and Air Velocity Distribution in an Aircraft Cabin Mockup Building and Environment, Vol. 43, pp Wang F.J., Lai C.M. and Zheng Y.R The influence of the air-circulation layout alternatives on air flow patterns in the processing area of a cleanroom Indoor and Built Environment. Vol. 18, pp Zhang, R., Tu G. and Ling J Study on biological contaminant control strategies under different ventilation models in hospital operating room Building and Environment. Vol. 43, pp Zhao, B. and Zhang Y Comparison of indoor aerosol particle concentration and deposition in different ventilated rooms by numerical method Building and Environment. Vol. 39, pp. 1-8 ISBN: COBEE2018-Paper255 page 768