A Markov chain model for predicting transient particle transport in enclosed environments

被引：64
作者：
Chen, Chun [1 ]
Liu, Wei [1 ,3 ]
Lin, Chao-Hsin [2 ]
Chen, Qingyan [1 ,3 ]
机构：
[1] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA
[2] Boeing Commercial Airplanes, Environm Control Syst, Everett, WA 98203 USA
[3] Tianjin Univ, Sch Environm Sci & Engn, Tianjin Key Lab Indoor Air Environm Qual Control, Tianjin 300072, Peoples R China
来源：
BUILDING AND ENVIRONMENT | 2015年 / 90卷
关键词：
Indoor environment; Computational fluid dynamics (CFD); Aerosol; Lagrangian; Eulerian; Unsteady-state; HUMAN EXHALED DROPLETS; AIRBORNE TRANSMISSION; CONTAMINANT TRANSPORT; INDOOR ENVIRONMENTS; MULTIZONE MODEL; AIR-FLOW; VENTILATION; DISPERSION; INFECTION; EXPOSURE;
D O I：
10.1016/j.buildenv.2015.03.024
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
Obtaining information about particle dispersion in a room is crucial in reducing the risk of infectious disease transmission among occupants. This study developed a Markov chain model for quickly obtaining the information on the basis of a steady-state flow field calculated by computational fluid dynamics. When solving the particle transport equations, the Markov chain model does not require iterations in each time step, and thus it can significantly reduce the computing cost. This study used two sets of experimental data for transient particle transport to validate the model. In general, the trends in the particle concentration distributions predicted by the Markov chain model agreed reasonably well with the experimental data. This investigation also applied the model to the calculation of person-to-person particle transport in a ventilated room. The Markov chain model produced similar results to those of the Lagrangian and Eulerian models, while the speed of calculation increased by 8.0 and 6.3 times, respectively, in comparison to the latter two models. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：30 / 36
页数：7
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