报告题目：Multiscale Physical Modelling and Al-Accelerated 3D Simulation of Urban Environments
报 告 人：Dr. Jie Zheng
报告时间：2026年9月4日（周五） 10:20-11:00
报告地点：藕舫楼724室
主 持 人：王曰朋 教授
报告摘要：
Urban environmental processes span a wide range of spatial and temporal scales, from regional atmospheric transport to building-scale flow and pollutant dispersion. This presentation introduces a framework integrating multiscale physical simulation with high-resolution artificial intelligence. An anisotropic adaptive-mesh atmospheric chemistry transport model based on Fluidity enables efficient multi-scale pollutant simulation, while building-resolving large-eddy simulation using PALM provides high-resolution urban meteorology and air-quality modelling. A 3D deep-learning surrogate further emulates PALM-generated urban PM2.5 fields at 10 m resolution, enabling rapid prediction while preserving major spatial and vertical structures. Together, these stages demonstrate a transition from adaptive multiscale physical modelling to building-resolving simulation and AI-accelerated modelling, providing a pathway towards efficient and scalable urban environmental digital twins and data-driven decision support.
报告人简介：
Dr. Jie Zheng is a Research Associate in the Department of Earth Science and Engineering at Imperial College London, where his research focuses on multiscale physical modelling and data-driven tools for urban environmental and carbon management. He received his PhD in Atmospheric Physics and Atmospheric Environment from the University of Chinese Academy of Sciences and has more than 15 years of experience in atmospheric modelling, adaptive-mesh methods and air-quality simulation. His research has included the development of the Fluidity-Chem anisotropic adaptive-mesh atmospheric chemistry transport model, high-resolution urban environmental modelling using PALM, and machine-learning approaches for rapid air-quality prediction and surrogate modelling. He has led and contributed to research projects funded by the National Key R&D Program of China, National Natural Science Foundation of China, and Ningbo Science and Technology Benefiting Project, with applications ranging from regional multi-species pollution transport to high-resolution urban air quality and smart-city environmental management.
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数学与统计学院
江苏省应用数学（南京信息工程大学）中心
江苏省系统建模与数据分析国际合作联合实验室
2026年9月3日
