A grid-merging operation to accelerate the Markov chain model in predicting steady-state and transient transmission of airborne particles

To accelerate the process of obtaining the faster-than-real-time information for both steady-state and transient particle transmission in the indoor or local atmospheric environment, a grid-merging operation has been developed as applying the Computational Fluid Dynamics (CFD) combined Markov chain model. A steady-state flow field was calculated in advance, and then the flow rate data were exported into MATLAB platform and preprocessed with matrixing process. The grid-merging operation combined Markov chain model therefore was realized in a computational resource saving way. Two particle transmission cases including both a constant particle releasing source and a pulsed particle releasing source were used to validate the simulation results, and the general trends of the particle concentration distributions agreed reasonably well with the experimental data. In addition, the computing time costs after the grid-merging operation can remarkably be reduced while maintaining an acceptable accuracy. Besides, it is crucial for the overall computing accuracy to select one appropriate time step size Δt for as many cells as possible within the whole computational domain.

[1]  Baskar Ganapathysubramanian,et al.  Quantifying mechanical ventilation performance: The connection between transport equations and Markov matrices , 2016 .

[2]  Nancy J. Brown,et al.  A Concentration Rebound Method for Measuring Particle Penetration and Deposition in the Indoor Environment , 2002 .

[3]  Shelly L. Miller,et al.  Environmental tobacco smoke particles in multizone indoor environments , 2001 .

[4]  Guangcai Gong,et al.  Numerical simulation of indoor suspension particles based on v2-f model , 2012 .

[5]  Bin Zhao,et al.  Effect of particle spatial distribution on particle deposition in ventilation rooms. , 2009, Journal of hazardous materials.

[6]  C Chen,et al.  Predicting transient particle transport in enclosed environments with the combined computational fluid dynamics and Markov chain method. , 2014, Indoor air.

[7]  Andrea R Ferro,et al.  Source strengths for indoor human activities that resuspend particulate matter. , 2004, Environmental science & technology.

[8]  Chi‐Hwa Wang,et al.  On the association between outdoor PM2.5 concentration and the seasonality of tuberculosis for Beijing and Hong Kong. , 2016, Environmental pollution.

[9]  Lin Lu,et al.  First order multivariate Markov chain model for generating annual weather data for Hong Kong , 2011 .

[10]  Bin Zhao,et al.  Numerical Investigation of Particle Diffusion in a Clean Room , 2005 .

[11]  Alvin C.K. Lai,et al.  Particle deposition indoors: a review , 2002 .

[12]  Runyu Yang,et al.  Modeling collective dynamics of particulate systems under time-varying operating conditions based on Markov chains , 2013 .

[13]  Tracy L. Thatcher,et al.  Effects of room furnishings and air speed on particle deposition rates indoors , 2002 .

[14]  A. Lai,et al.  Modeling particle distribution and deposition in indoor environments with a new drift–flux model , 2006 .

[15]  Experimental investigation of jet-induced resuspension of indoor deposited particles , 2016 .

[16]  Li Chen,et al.  A seasonal study of polycyclic aromatic hydrocarbons in PM(2.5) and PM(2.5-10) in five typical cities of Liaoning Province, China. , 2010, Journal of hazardous materials.

[17]  W. Nazaroff.  Indoor particle dynamics. , 2004, Indoor air.

[18]  Shaodong Xie,et al.  Source apportionment of PM2.5 in Beijing in 2004. , 2007, Journal of hazardous materials.

[19]  Sture Holmberg,et al.  Modelling of the Indoor Environment – Particle Dispersion and Deposition , 1998 .

[20]  Roger Ghanem,et al.  Multiscale Markov models with random transitions for energy demand management , 2013 .

[21]  Qingyan Chen,et al.  Experimental measurements and numerical simulations of particle transport and distribution in ventilated rooms , 2006 .

[22]  Q Chen,et al.  Air flow and particle control with different ventilation systems in a classroom. , 2003, Indoor air.

[23]  Jyh-Cherng Chen,et al.  Concentrations of ambient air particulates (TSP, PM2.5 and PM2.5-10) and ionic species at offshore areas near Taiwan Strait. , 2006, Journal of hazardous materials.

[24]  R. L. Jensen,et al.  Influence of air stability and metabolic rate on exhaled flow. , 2015, Indoor air.

[25]  R. L. Jensen,et al.  Measuring the exhaled breath of a manikin and human subjects. , 2015, Indoor air.

[26]  Q. Duan,et al.  Seasonal Variation of Newly Notified Pulmonary Tuberculosis Cases from 2004 to 2013 in Wuhan, China , 2014, PloS one.

[27]  Wei Liu,et al.  A Markov chain model for predicting transient particle transport in enclosed environments , 2015, Building and Environment.

[28]  Chao-Hsin Lin,et al.  Advanced turbulence models for predicting particle transport in enclosed environments , 2012 .

[29]  Baskar Ganapathysubramanian,et al.  Constructing Markov matrices for real-time transient contaminant transport analysis for indoor environments , 2015, Building and Environment.

[30]  Bin Zhao,et al.  Particle dispersion and deposition in ventilated rooms: Testing and evaluation of different Eulerian and Lagrangian models , 2008 .

[31]  Xijin Xu,et al.  The role of the PM2.5-associated metals in pathogenesis of child Mycoplasma Pneumoniae infections: a systematic review , 2016, Environmental Science and Pollution Research.

[32]  William W. Nazaroff,et al.  Particle Penetration Through Building Cracks , 2003 .

[33]  Qingyan Chen,et al.  Comparison of the Eulerian and Lagrangian methods for predicting particle transport in enclosed spaces , 2007 .

[34]  Rachael M. Jones,et al.  Benchmarking of a Markov multizone model of contaminant transport. , 2014, The Annals of occupational hygiene.

[35]  M. Nicas,et al.  Markov modeling of contaminant concentrations in indoor air. , 2000, AIHAJ : a journal for the science of occupational and environmental health and safety.

[36]  De-Ling Liu,et al.  Modeling pollutant penetration across building envelopes , 2001 .