发布时间：2024-02-23
姓名：刘炜
职称：英才教授（优秀青年基金海外）
系别：建筑环境与设备工程系
专业：供热、通风与空调工程
主要研究方向：
建造环境的逆向设计、控制及优化，快速计算流体力学，计算流体力学与机器学习
本人有引进人才博/硕士生招生特别名额，欢迎有志青年联系加盟。
电子邮箱：weiliu@tju.edu.cn
教育及工作经历：
教育经历
2009/07，学士，天津大学，建筑环境与设备工程
2014/05，硕士，普渡大学，机械工程
2016/07，博士，天津大学，供热、供燃气、通风及空调工程
2017/08，博士，普渡大学，机械工程
工作经历
2017/10 – 2019/01，浙江大学，助理教授
2019/01 – 2022/12，KTH瑞典皇家理工学院，助理教授
2023/01 – 2023/12，KTH瑞典皇家理工学院，副教授（终身）
2024/01至今，天津大学，教授
获奖情况：
国家自然科学基金优秀青年科学基金项目（海外），2022
全球大学生数模竞赛最高奖项特等奖和冠名INFORMS奖, 2019
天津市优秀博士论文, 2019
ROOMVENT国际会议最佳论文奖, 2018
校级优秀博士学位论文, 天津大学, 2017
普渡大学Bilsland论文奖学金 (US$ 19,000 plus tuition), Purdue University, 2016
博士研究生国家奖学金 (RMB 30,000), 天津大学, 2012
美国暖通空调工程师协会RP-1493 CFD竞赛第一名 (US$20,000), ASHRAE, 2012
Grant-in-Aid Award for Graduate Students (US$10,000), ASHRAE, 2011
第16届“人工环境工程学科奖学金”一等奖, 2008
天津大学优异生, 2008
学术兼职：
美国采暖与制冷空调工程师协会（ASHRAE）会员
国际室内空气品质学会(ISIAQ)会员
欧洲暖通协会REHVA 技术与研究委员会核心成员（SWE）
主讲课程：
工程热力学、建筑环境的分析与设计
在研项目（近五年）：
1、国家十四五重点研发计划课题“居住建筑及社区内病原微生物气溶胶传播机理及指标体系研究”（2023-2027）
2、“Faster-than-real-time and high-resolution simulation of fluid flow in engineering applications: indoor climate as a pilot”, Digital Futures Research Pairs project（2023-2024）
3、“AI-based prediction of urban climate and its impact on built environments”, Digital Futures and C3.ai Digital Transformation Institute (DTI) （2021-2022）
4、“Covid-19 laden bioaerosol generation, transport, and its removal in public washroom”, STINT (Stiftelsen för internationalisering av högre utbildning och forskning)（2021-2023）
5、浙江大学-阿里巴巴前沿技术联合研究中心“面向数据中心运维的开源 CFD仿真平台开发”（2021-2022）
6、“Improved assessment of wind-induced air infiltration in historic buildings”, Energimyndigheten (No. 50057-1)（2020-2023）
7、国家自然科学基金青年项目“耦合基于CFD伴随方法和积耗散理论逆向设计建造环境”（2019-2021）
8、“Toxicity Burden associated with Fine Ambient Particulate Matter (PM2.5) in Human Respiratory System”, Zhejiang University - University of Illinois at Urbana-Champaign Institute Research Program（2019-2020）
主要论文、成果：
2024
71. Liu, F., Liu, W.*, Long, Z., and Zhang, T. Evolution of particle size distribution and water content for oily particles in machining workshops. Journal of Building Engineering, 2024, 10.1016/j.jobe.2024.108542.
2023
70. Wang, Y., Li, J., Liu, W., Zhang, S., Dong, J., and Liu, J., Prediction of urban airflow fields around isolated high-rise buildings using data-driven non-linear correction models. Building and Environment, 2023, 110894.
69. Calzolari, G. and Liu, W.*, Deep learning to develop zero-equation based turbulence model for CFD simulations of the built environment. Building Simulation, 2023, 10.1007/s12273-023-1083-4.
68. Liu, F., Chen, H., Yuan, H., Zhang, T., and Liu Wei.*, Shape optimization of the exhaust hood in machining workshops by a discrete adjoint method. Building and Environment, 2023, 110764.
67. Liu, W., Lian, S., Fang, X., Shang, Z., Wu, H., Zhu, H., and Hu, S., An open-source and experimentally guided CFD strategy for predicting air distribution in data centers with air-cooling. Building and Environment, 2023, 110542.
66. Ma, S., Liu, W., Dong, J., Meng, C., and Liu, J., Comparison of the time-dependent characteristics between particle mass and particle number emissions during oil heating and emission mitigation strategies. Building and Environment, 2023, 242, 110511.
65. Kabanshi, A., Choonya, G., Ameen, A., Liu, W. and Mulenga, E., Windows of opportunities: orientation, sizing and PV-shading of the glazed area to reduce cooling energy demand in sub-Sahara Africa. Energies, 2023, 16(9), p.3834.
64. Li, P., Liu, W., and Zhang, T. CFD modeling of dynamic airflow and particle transmission in an aircraft lavatory. Building Simulation, 2023, 16, 1375-1390.
63. Lei, L. and Liu, W.*, Inverse identification model for release rates of multiple gaseous pollution sources in an aircraft cabin. Indoor and Built Environment, 2023, 1420326X231170787.
62. Wang, Y., Guo, Y., Hao, W., Liu, W., and Long, Z., Simulation study of the purification system for indoor oil mist control in machining factories. Building Simulation, 2023, 16, 1361-1374.
61. Chen, Z., O’Neill, Z., Wen, J., Pradhan, O., Yang, T., Lu, X., Lin, G., Miyata, S., Lee, S., Shen, C., Chiosa, R., Piscitelli, M.S., Capozzoli, A., Hengel, F., Kührer, A., Pritoni, M., Liu, W., Clauß, J., Chen, Y., and Herr, T., A review of data-driven fault detection and diagnostics for building HVAC systems. Applied Energy, 2023, 339, 121030.
60. Ma, S., Liu, W., Meng, C., Dong, J. and Zhang, S., 2023. Temperature-dependent particle mass emission rate during heating of edible oils and their regression models. Environmental Pollution, 2023, 323,121221.
59. Sun, R., Liu, J., Lai, D.*, and Liu, W.* Building form and outdoor thermal comfort: inverse design the microclimate of outdoor space for a kindergarten. Energy and Buildings, 2023, 112824.
2022
58. Liu, W., Zhang, T., and Lai, D. Inverse design of a thermally comfortable indoor environment with a coupled CFD and multi-segment human thermoregulation model. Building and Environment, 2022, 227: 109769.
57. Lei, L., Wu, B., Fang, X., Chen, L., Wu, H., and Liu, W.* A dynamic anomaly detection method of building energy consumption based on data mining technology. Energy, 2022, doi.org/10.1016/j.energy.2022.125575.
56. Lei, L., Zheng, H., Xue, Y., and Liu, W.* Inverse modeling of thermal boundary conditions in commercial aircrafts based on Green's function and regularization method. Building and Environment, 2022, 217, 109062.
55. Liu, Y., Long, Z., and Liu, W. A semi-empirical mesh strategy for CFD simulation of indoor airflow. Indoor and Built Environment, 2022, https://doi.org/10.1177/1420326X221089825.
54. Lei, L. and Liu, W.* Predictive control of multi-zone variable air volume air-conditioning system based on radial basis function neural network. Energy and Buildings, 2022, 261, 111944.
53. Ma, S., Liu, W., Dong, J., Liu, J., and Wang, Z. Indoor thermal environment in a rural dwelling heated by air-source heat pump air-conditioner. Sustainable Energy Technologies and Assessments, 2022, 51, 101948.
2021
52. Dai, T., Liu, S., Liu, J., Jiang, N., Liu, W., and Chen, Q. Evaluation of fast fluid dynamics with different turbulence models for predicting outdoor airflow and pollutant dispersion, Sustainable Cities and Society, 2022, 77, 103583.
51. Zheng, S., Zhai, Z., Wang, Y., Xue, Y., Duanmu, L., and Liu, W. Evaluation and comparison of various fast fluid dynamics modeling methods for predicting airflow around buildings. Building Simulation, 2022, 15, 1083-1095.
50. Hu, M., Liu, W., Xue, K., Liu, L., Liu, H., and Liu, M. Comparing calculation methods of state transfer matrix in Markov chain models for indoor contaminant transport. Building and Environment, 2022, 297,108515.
49. Liu, W.*, Sun, H., Lai, D., Xue, Y., Kabanshi, A., and Hu, S. Performance of fast fluid dynamics with a semi-Lagrangian scheme and an implicit upwind scheme in simulating indoor/outdoor airflow. Building and Environment, 2022, 207, 108477. https://doi.org/10.1016/j.buildenv.2021.108477.
48. Calzolari, G. and Liu, W.* Deep learning to replace, improve, or aid CFD analysis in built environment applications: a review. Building and Environment, 2021, 206, 108315. https://doi.org/10.1016/j.buildenv.2021.108315.
47. Li, S., Yang, J., and Liu, W.* Estimation of aerator air demand by an embedded multi-gene genetic programming. Journal of Hydroinformatics, 2021, 23 (5): 1000-1013. https://doi.org/10.2166/hydro.2021.037.
46. Xue, J., Liu, W., and Liu, K. Influence of thermal environment on attendance and adaptive behaviors in outdoor spaces: a study in a cold-climate university campus. International Journal of Environmental Research and Public Health, 2021, 18(11), 6139; https://doi.org/10.3390/ijerph18116139.
45. Lei, L., Chen, W., Wu, B., Chen, C., and Liu, W.* A building energy consumption prediction model based on rough set theory and deep learning algorithms. Energy and Buildings, Volume 240, 2021, 110886.
2020
44. Xue, J., You, R., Liu, W., Chen, C., and Lai, D. Applications of local climate zone (LCZ) classification scheme to improve urban sustainability. Sustainability, 2020, 12(19), 8083.
43. Liu, W., van Hooff, T., An, Y., Hu, S., and Chen, C. Modeling transient particle transport in transient indoor airflow by fast fluid dynamics with the Markov chain method. Building and Environment, 186, 2020, 107323.
42. Sun, J., Liu, W., Long, Z., Zhang, H., and Pan, W. Transmission and exposure of kitchen particles: a case study in an apartment. Indoor and Built Environment, 2020, doi: 10.1177/1420326X20942579.
41. Chen, S., Zhu, Y., Chen, Y., and Liu, W.* Usage strategy of phase change materials in plastic greenhouses, in hot summer and cold winter climate. Applied Energy, 227, 2020, 115416.
40. Lai, D., Lian, Z., Liu, W., Guo, C., Liu, W., Liu, K., and Chen, Q. A comprehensive review of thermal comfort studies in urban open spaces. Science of the Total Environment, 2020, doi: 10.1016/j.scitotenv.2020.140092.
39. Liu, K., Nie, T., Liu, W., Liu, Y., and Lai, D. A machine learning approach to predict outdoor thermal comfort using local skin temperatures. Sustainable Cities and Society, 2020, doi: 10.1016/j.scs.2020.102216.
2019
38. Lei, L., Chen, W., Xue, Y., and Liu, W.* A comprehensive evaluation method for indoor air quality of buildings based on rough sets and a wavelet neural network. Building and Environment, 162, 2019, 160296, doi: 10.1016/j.buildenv.2019.106296.
37. Xue, Y., Liu, W.*, Wang, Q., and Bu, F. Development of an integrated approach for the inverse design of built environment by a fast fluid dynamics-based generic algorithm. Building and Environment, 160, 2019, 106205, doi: 10.1016/j.buildenv.2019.106205.
36. Liu, W., You, R., and Chen, C. Modeling transient particle transport by fast fluid dynamics with the Markov chain method. Building Simulation, 2019, 12: 881-889.
35. Wei, Y., Liu, W., Xue, Y., Zhai, Z., Chen, Q., and Zhang, T. Inverse design of aircraft cabin ventilation by integrating three methods. Building and Environment, 2019, 150: 33-43.
