
Li, S., Yang, J., and Liu, W.* Estimation of aerator air demand by an embedded multi-gene genetic programming. and Liu, W.* Deep learning to replace, improve, or aid CFD analysis in built environment applications: a review. Performance of fast fluid dynamics with a semi-Lagrangian scheme and an implicit upwind scheme in simulating indoor/outdoor airflow. Liu, W.*, Sun, H., Lai, D., Xue, Y., Kabanshi, A., and Hu, S.


Comparing calculation methods of state transfer matrix in Markov chain models for indoor contaminant transport. Hu, M., Liu, W., Xue, K., Liu, L., Liu, H., and Liu, M.

Accepted by Building Simulation, 2021.ĥ0. Evaluation and comparison of various fast fluid dynamics modeling methods for predicting airflow around buildings. 51, Zheng, S., Zhai, Z., Wang, Y., Xue, Y., Duanmu, L., and Liu, W.
