Conference Paper
Proceedings of SimBuild Conference 2024
Effects of Urban Morphology on Pedestrian Level Wind Environment and Air Temperature: Using Simulation and Explainable Machine Learning
Effects of Urban Morphology on Pedestrian Level Wind Environment and Air Temperature: Using Simulation and Explainable Machine Learning
Cui Xue 1, Li Yu 2,3, Pengyuan Shen 41 Department of Building and Real Estate, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong, China 2 School of Architecture, Harbin Institute of Technology, Harbin, China 3 Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Ministry of Industry and Information Technology, Harbin, China 4 School of Architecture, Harbin Institute of Technology, Shenzhen, ChinaAbstract: Urban morphology plays a crucial role in affecting pedestrian level wind velocity and air temperature. Most existing studies utilized the CFD method to simulate environmental parameters at the pedestrian level, while using statistical analysis to assess the impact of urban morphology. Simulation has high requirements in computational time, input parameters, and modeler expertise. Statistical analysis results highly rely on the pre-designed scenarios while lacking a profound interpretation. The study addressed these gaps by using CFD simulation data to establish two separate machine learning models for quickly predicting pedestrian level wind velocity and air temperature. Results showed that XGBoost-based models achieved better performance than LightGB-based models. Then, explainable SHAP was applied to the optimal prediction models for investigating the effect of urban morphology on pedestrian level wind velocity and air temperature. SHAP results revealed that the location of sidewalks from the building array center has a more significant impact on wind velocity and air temperature than the street width, building height and width, and orientation angle. In addition, the study explored the interaction effect of urban morphology-related design variables on pedestrian level wind velocity and air temperature. Keywords: Wind Velocity, Air Temperature, Urban Morphology, Thermal Comfort, Computational Fluid Dynamics, Machine Learning, SHapley Additive exPlanationsPages: 267 - 277 Paper: