1、4729 Numerical Analysis of the Movement of Biological Particles in Two Adjacent Rooms Bin Zhao, Ph.D. Ying Zhang Xianting Li, Ph.D. Member ASHRAE ABSTRACT Severe acute respiratory syndrome (SARS) is a recently described illness of humans with a high case fatality rate that has spread widely since No
2、vember 2002. As SARS und many other diseases may be transmitted by biological airborne particles, it is important to analyze the movement of biological particles indoors to protect the indoor environment from biological pollution. In this papel: the movement of biological particles in two adjacent r
3、ooms is numerically studied under cross ventilation. The cases of different air exchange rates and initial positions of particles are analyzed und compared numerically. The discrete trajectory model is adopted to simu- late particle tracks, while the Eulerian method for solving continuousfluidflow i
4、s combined. The results show that the air exchange rate and initial positions of the particles are two key factors influencing the indoor environment of the rooms. For the cases presented, the number of biological particles in the internal room increases with the increase of air exchange rate of the
5、 external room. Furthermore, if the particles are closer to the conjoined opening of the two rooms, the number of the particles may be more. INTRODUCTION Severe acute respiratory syndrome (SARS) is a recently described illness of humans with a high case fatality rate that has spread widely since Nov
6、ember 2002. By late April 2003, over 4,300 SARS cases and 250 SARS-related deaths from over 25 countries around the world were reported by the World Health Organization (WHO). Epidemiologic studies indicate that SARS may be transmitted by airborne particles that contain the novel coronavirus (SARS-C
7、oV) (Rota et al. 2003). The experience in Guangdong Province, China, indicates that natural ventilation is helpful for defending against SARS. However, most buildings have adjacent external and internal rooms, where the natural ventilation of the external room may cause adverse effect on the intemal
8、 room, as the biological particles may move from external room to internal room under natural ventilation. Thus, the movement of biological particles in two adjacent rooms needs to be studied to analyze their effect on the indoor environment as a kind of biological pollu- tion. It is known that the
9、numerical method (also called computational fluid dynamics CFD) can provide detailed information of airflow and particle movement in ventilated spaces, while it is difficult to examine the movement of parti- cles by experimental measurements. The purpose of this paper is to study the movement of bio
10、logical particles generated by human bodies in two adjacent rooms under cross-ventilation by a three-dimensional numerical method so that the indoor environment may be analyzed and evaluated. The cases of different air exchange rates and initial positions ofparticles are analyzed. MATHEMATICAL MODEL
11、 For the cross-ventilation studied in this paper, only isothermal condition is considered. The mathematical model includes two parts: the model for continuous phase (air) and the model for discrete phase (particles). Airflow Model Governing Equations and Numerical Methods. The air in the room is con
12、sidered a continuous fluid, which is governed by the conservation equation. For indoor air turbulence, the Reynolds averaged Navier-Stokes (RANS) Bin Zhao is a postdoctoral fellow in the Department of Building Science and the Department of Engineering Mechanics, and Ying Zhang is a graduate student
13、and Xianting Li is a professor in the Department of Building Science, Tsinghua University, Beijing, China. 370 02004 ASHRAE. equations may get closure by applying turbulence models. Here the k-E turbulence model is employed since it is widely used for indoor airflow simulation, and good agreement be
14、tween simulated results and measured data have been reported (Chen 1995). The governing equations can be written in the general format as follows: at ?(pq) + div(php-r,gradq) = S, (1) where cp represents each of the three velocity components, u, v, and w (ds): the kinetic energy of turbulence, k (m2
15、/s2), the dissipation rate of the kinetic energy of turbulence, E (m2/s3), and air enthalpy, h (jkg). rV is the effective exchange coeffi- cient for the dependent variable cp, and SV is the source term of the general equation. The formation of S, and the turbulence parameters of the k- that is, mass
16、 flow boundaries are specified to ensure the mass flow rate out of the domain is the same as the mass flow rate into the flow domain. Wall functions are applied to describe the turbulent flow properties in the near wall region. More details are given by Launder and Spalding (1 974). Particle Traject
17、ory Model Equations of Motion. The discrete trajectory approach (Lagrangian method) is employed in the particle trajectory model. The Lagrangian approach splits the particle phase into a representative set of individual particles and tracks these particles separately through the flow domain by solvi
18、ng the equations of particle movement. The following assumptions are used: a. Heat and mass transfer between the air and the particles is neglected. b. There are no particle rebounds on solid surfaces, such as walls, floors and ceilings. c. There is no particle coagulation in the particle deposition
19、 procedure. d. All particles are spherical solid particles. e. The effect of particles on turbulence is not considered, as it is believed that the low particle loadings and compara- tively small particle settling velocities have a very small effect compared to the high inflow turbulence levels (Elg-
20、 hobashi 1994). The equations of individual particle movement come directly from Newtons second law, where upi is particle velocity in i direction (ms), and Fi is all external forces exerted on the particle er unit particle mass) in i direction (m/s2). Fi may be written as where ui and upi are the v
21、elocities of air and particle, respec- tively (ms); p is the molecular viscosity of air (kg/m*s); p is the density of air (kg/m3); dp is the particle diameter (m); pp is the density of particle (kg/m3); Re is the particle Reynolds number; and C, is the drag coefficient. The first term of the right-h
22、and side of Equation 3 is the drag force per unit particle mass (m/s2). Re is defined by C, is the drag coefficient and c, = a,+-+ a2 a Re even the initial positions are the same (this is shown in Figure 5). As a result, the particles may suspend, escape, or deposit on the surfaces, and the number o
23、f particles in different rooms is different. We are concerned most with the suspended particles because if humans are exposed to them, their health could be affected. Thus, the figures show the suspended particles at different times. Figure I Schematic of the two adjacent rooms and the initial posit
24、ions ofparticles (A, B, and C). 372 ASHRAE Transactions: Research 160 - - -LocationC Parfide number in extemai room (5 ACH) 160 120 80 40 Paiticle number in external room (20 ACH) i i- Location B - - -Locatime o O 100 200 300 160 120 80 40 O Particle mber in eaernal room (50 ACH) Particle number in
25、irdemal room (5 ACH 120 r I t n ao f c al a F 40 n O Location A I_ 1 O0 200 %me (s) 300 Particfe number in internal room (20 ACH) 100 - Location A Location B - - -LocationC - O 50 100 150 200 250 300 TlTE(S) 4 Particle number in ntemai room (50 ACH) Figure 2 Comparison ofparticle numbers in the two
26、rooms for diflerent initial positions of the particles. ASHRAE Transactions: Research 373 Particle number in extemai mom (Location A) Paiticle number in internal room (Location A) 5 ACH - -20ACH n -5ACH .* h - a -20ACH a - - -5OACH . . 0 I I, 1. O 50 100 150 200 250 300 Time (s) b) Particle number i
27、n irternal room (Location 9) O I O0 200 300 Time (s) 4 Partide nunber inexternal room (Location B) 160 120 k e a, 80 32 5 s - O m R 40 O 120 2 80 5 c a) o e 2 40 - .- O . ._. -5 ACH - - -50ACH I l l O 50 100 150 200 250 300 Time (s) c O 100 200 300 Time(s) 4 Partide number in external room (Location
28、 C) Parcle number ininternai room (LocationC) 160 1 -5ACH - 5 ACH -20f4CH 40 i I O 1 O0 MO 300 Tillle(S) f) Figure 3 Comparison ofparticle numbers in the two rooms for different air exchange rates. ASHRAE Transactions: Research 374 - 0.2 mis _ (a) 5 ACH, (b) 20 ACH, (c) 50 ACH. ASHRAE Transactions:
29、Research 375 a) 5 ACH (particle trapped by the wall) -Y b) 20 ACH (pancle suspended in the external room) c) 50 ACH (particle escaped from exhaust) Figure 5 Comparison ofparticle tracks for different air exchange rates. 376 ASHRAE Transactions: Research Figure 2 shows that the initial position of th
30、e particles strongly influences the indoor environment of the two rooms. As the particles are closer to the door, which is close to the internal room, there are more particles in the internal room. For instance, the number of particles in the intemal room for location B is much more than that of the
31、 other two cases. And, as time elapses, the particle number will reduce as some of them will escape from the exhaust. However, the number of particles in the external room is reduced as the particles are closer to the internal room. It is reasonable since it is easier for the particles to enter the
32、internal room by cross-ventilation if they are closer to the internal room. Figure 3 shows that a larger air exchange rate causes fewer particles in the external room, which may be helpful for improving the indoor envi- ronment. However, it causes adverse effect on internal room for this case. Figur
33、e 3 indicates that larger air exchange rates of contaminated unfiltered air results in more particles suspended in the internal room. It is not desirable for defend- ing the indoor environment and the occupants against infec- tious diseases (for example, the SARS) under this circumstance. Figure 5 f
34、urther gives one particle track under different air exchange rates. The particle has the same initial position. It shows that for the same initial positions of parti- cles, the particles movement and distribution may differ significantly. These results imply that although natural ventilation (cross-
35、ventilation) may be helpful for defending the spread of SARS, some cases exsist where the ventilation may cause adverse effects on the environment inside some certain zones of the buildings. The case presented in the paper is such a case. It indicates that if a pollutant source (e.g., a patient carr
36、ying infectious viruses who may or may not be aware of hisher infection) is in the external room, the airflow caused by cross- ventilation may carry the particles with the virus into the inter- nal room and, thus, pollute the interior space. More airflow rate and closer location to the intemal room
37、of the particles may cause more particles to be suspended inside the internal room. CONCLUSIONS Numerical analysis of the movement of biological parti- cles in two adjacent rooms by cross-ventilation under different air exchange rates and particle initial positions is performed in this study. The fo
38、llowing conclusions may be drawn based on this particular study: 1. The initial position of the biological particles is an impor- tant factor that influences the indoor environment. The biological pollution in the internal room may be more seri- ous if the particles are closer to the room-when cross
39、- ventilation is formed for the adjacent rooms-which flows through from the external room to internal room. Air exchange rate is another important factor that influ- ences the indoor environment of the adjacent room under cross-ventilation. For the cases presented in this study, a larger air exchang
40、e rate will cause fewer particles in the external room but more particles in the internal room. 2. ACKNOWLEDGMENT This study is financially supported by the Natural Science Foundation of China (Grant No. 50346007) and Beijing Key Laboratory of Heating, Gas Supply, Ventilating and Air Conditioning En
41、gineering. REFERENCES Chen, Q. 1995. Comparison of different models for indoor airflow computation. Numerical Heat Transfer; Part B, Fundamentals, 28:3 5 3-369. Elghobashi, S. 1994. On predicting particle-laden turbulent flows. Applied Scientzfic Research 52:309-329. Fluent Inc. 1997. The Manual ofF
42、luent 5.5 (USA). Launder, B.E., and D.B. Spalding. 1974. The numerical computation of turbulence flows. Computing Methods Applied Mechanical Engineering 3 :269. Li, A., and G. Ahmadi. 1992. Dispersion and deposition of spherical particles from point sources in a turbulent channel flow. Aerosol Scien
43、ce and Technology 16:209- 226. Morsi, S.A., and A.J. Alexander. 1972. An investigation of particle trajectories in two-phase flow systems. J. Fluid Mech. 55(2):193-208. Patankar, S.V. 1980. Numerical Heat Transfer and Fluid Flow. Washington, D.C.: Hemisphere. Rota, P.A., M.S. Oberste, S.S. Monroe, W
44、.A. Nix, R. Cam- pagnol;, J.P. Icenogle, S. Penaranda, B. Bankamp, K. Maher, M. Chen, Su Tong, A. Tamin, L. Lowe, M. Frace, J. DeRisi, Q. Chen, D. Wang, D. Derdman, T.C.T. Peret, C. Burns, T.G. Ksiazek, P.E. Rollin, A. Sanchez, S. Liffick, B. Holloway, J. Limor, K. McCaustland, O. Olsen-Rassmussen,
45、R. Fouchier, S. Gunther, A.D.M.E. Osterhaus, C. Drosten, M.A. Pallansch, L.J. Anderson, and W.J. Bellini. 2003. Characterization of a novel coro- navirus associated with severe acute respiratory syn- drome. Science Exspress 2003.1 O. 1 126/Science, 1085952. Saffman, P.G. 1965. The lift on a small sp
46、here in a slow shear flow. J. Fluid Mech. 22385- 400. YU, X. 2001, Modern Airborne Microbiology. Beijing: Peo- ples Military Medical Publisher. (in Chinese). Zhao, B., Y. Zhang, X. Li, X. Yang, and D. Huang. 2004. Comparison of indoor aerosol particle concentration and deposition in different ventilated rooms by numerical method. Building and Environment 39(1): 1-8. ASH RAE Transactions: Research 377
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