CaoSJ.Challenges of using CFD simulation for the design and online control of ventilation systems. Indoor Built Environ2019;
28: 3–6.
2.
LuoNWengWXuXFuM.Human-walking-induced wake flow: PIV experiments and CFD simulations. Indoor Built Environ2017;
27: 1069–1084.
3.
WangYHuangYZhouYShuYLiuJ.Experimental study on one-side confined jets from a parallel-flow outlet in a push-pull ventilation system. Indoor Built Environ2013;
24: 73–86.
4.
TakeuchiJKurabuchiTYoshinoHLeeS.Performance comparison of conventional and local computer room air-conditioning systems in data centres by CFD analysis. Indoor Built Environ2016;
26: 238–247.
5.
WangYCaoYMengX.Energy efficiency of industrial buildings. Indoor Built Environ2019;
28: 293–297.
6.
WangYCaoZ.Industrial building environment: old problem and new challenge. Indoor Built Environ2017;
26: 1035–1039.
7.
ChenQLeeKMazumdarSPoussouSWangLWangMZhangZ.Ventilation performance prediction for buildings: model assessment. Build Environ2010;
45: 295–303.
8.
WangHZhaiZ.Analyzing grid independency and numerical viscosity of computational fluid dynamics for indoor environment applications. Build Environ2012;
52: 107–118.
9.
GeorgesLThalfeldtMSkreibergØFornariW.Validation of a transient zonal model to predict the detailed indoor thermal environment: case of electric radiators and wood stoves. Build Environ2019;
149: 169–181.
10.
AbadieMCamargoMMendoncKBlondeauP.Improving the prediction of zonal modeling for forced convection airflows in rooms. Build Environ2012;
48: 173–182.
11.
WangLChenQ.Applications of a coupled multizone and CFD model to calculate airflow and contaminant dispersion in built environment for emergency management. HVAC&R Res2008;
14: 925–939.
12.
WangLChenQ.Evaluation of some assumptions used in multizone airflow network models. Build Environ2008;
43: 1671–1677.
13.
WangQPanYZhuMHuangZTianWZuoWHanXXuP.A state-space method for real-time transient simulation of indoor airflow. Build Environ2017;
126: 184–194.
14.
ChenQXuW.A zero-equation turbulence model for indoor airflow simulation. Energy Build1998;
28: 137–144.
15.
ZuoWChenQ.Real time or faster-than-real-time simulation of airflow in buildings. Indoor Air2009;
19: 33–44.
16.
ZuoWChenQ.Simulations of air distribution in buildings by FFD on GPU. HVAC&R Res2010;
16: 785–798.
17.
WangJZhangTZhouHWangS.Inverse design of aircraft cabin environment using computational fluid dynamics-based proper orthogonal decomposition method. Indoor Built Environ2017;
27: 1379–1391.
18.
FontaniniAVaidyaUPassalacquaAGanapathysubramanianB.Contaminant transport at large Courant numbers using Markov matrices. Build Environ2017;
112: 1–16.
19.
JonesRNicasM.Experimental evaluation of a Markov multizone model of particulate contaminant transport. Ann Occup Hyg2014;
58: 1032–1045.
20.
ShaoXWangKLiX.Rapid prediction of the transient effect of the initial contaminant condition using a limited number of sensors. Indoor Built Environ2019;
28: 322–334.
21.
CaoSJMeyersJ.On the construction and use of linear low-dimensional ventilation models. Indoor Air2012;
22: 427–441.
22.
CaoSJMeyersJ.Fast prediction of indoor pollutant dispersion based on reduced-order ventilation models. Build Simul2014;
8: 415–420.
23.
MegriANaqaI.Prediction of the thermal comfort indices using improved support vector machine classifiers and nonlinear kernel functions. Indoor Built Environ2014;
25: 6–16.
24.
ChaoJMuXXueYLiFLiWLinCPeiJChenQ.A modified tracer-gas decay model for ventilation rate measurements in long and narrow spaces. Indoor Built Environ2013;
23: 1012–1020.
25.
ZhangTYouX.The use of genetic algorithm and self-updating artificial neural network for the inverse design of cabin environment. Indoor Built Environ2015;
26: 347–354.
26.
RenJCaoSJ.Incorporating online monitoring data into fast prediction models towards the development of artificial intelligent ventilation systems. Sustain Cities Soc2019;
47: 104189.
27.
CaoSJRenC.Ventilation control strategy using low-dimensional linear ventilation models and artificial neural network. Build Environ2018;
144: 316–333.
