学术报告（一）
报告题目：Development and Applications of Combined Finite-Discrete Element Method and Fluid-Solid Coupling Model（有限离散元及流固耦合数值模拟方法及其应用）
报告人：Jiansheng Xiang
报告时间：2022年10月12日（周三）15:30-16:45
报告地点：腾讯会议627-291-238
报告人简介：
Dr. Jiansheng Xiang is a research fellow in the Applied Modelling & Computation Group at Imperial College London. He has been working in the theories and development of the combined finite-discrete element method (FDEM) and fluid-solid coupling model and applied them in diverse scientific and engineering problems in computational solid/fluid mechanics, fluid-solid interaction, heat transfer, fracture mechanics, and turbulent flow. He has published 50+ articles in leading engineering and computational physics journals in addition to 70+ conference papers. This talk will be about the development of FDEM and fluid-solid coupling model and their applications in several engineering problems (e.g., failure of concrete armour units for breakwater).
Dr. Jiansheng Xiang，帝国理工学院研究员。主要从事有限离散元、流固耦合模拟程序开发与应用，涉及到计算固体力学、流体力学、流固相互作用、热传递、断裂力学、湍流等多个领域内的前沿科学与工程问题，是有限离散元程序Solidity（该程序已成功应用于非连续、颗粒、断裂、破碎等力学问题）的主要开发者。在国际主流期刊发表50余篇SCI论文，在主流国际会议作学术报告70余次。本次汇报的主要内容包括有限离散元与流固耦合数值模拟理论与方法，及其在一系列工程问题（如防波堤混凝土块破坏）中的应用。
学术报告（二）
报告题目：Real-Time Predictive Modelling of Environmental Problems Using Machine Learning and Data Assimilation（基于机器学习与数据同化的实时预测模型及其在环境问题中的应用）
报告人：Fangxin Fang
报告时间：2022年10月12日（周三）16:45-18:00
报告地点：腾讯会议627-291-238
报告人简介：
Dr. Fangxin Fang is a senior research fellow in the Applied Modelling & Computation Group at Imperial College London, and executive manager of data assimilation laboratory at the Data Science Institute, Imperial. Her research areas focus on predictive modelling using machine learning, data assimilation methods, model reduction and optimal controls in geophysical models as well as applications in ocean, atmospheric, multiphase flows and environmental problems. The application areas include natural hazard (e.g., flooding) environmental issues (e.g., air pollution), ocean and engineering problems. She is currently the scientific lead of a research project on adaptive mesh modelling for ocean flows and air pollution. She has published 75+ journal papers and given over 50+ talks at SIAM, AGU, EGU, etc. conferences. This talk will introduce the theories and development of the real-time large-scale predictive modelling based on machine leaning and data assimilation as well as applications in natural hazard and environmental problems such as flooding and air pollution.
Dr. Fangxin Fang，帝国理工学院高级研究员，数据科学研究中心数据同化实验室执行主管。主要从事基于机器学习、数据同化、模型降阶、优化控制等方法的预测模型及其在自然灾害（如洪水）、环境问题（如空气污染）、海洋与工程问题中的应用，作为洋流与空气污染的自适应网格模拟课题主要负责人。发表70余篇SCI论文，在国际主流学术会议（如SIAM、AGU、EGU、AOGS）汇报50余次。本次汇报的主要内容包括基于机器学习和数据同化的大尺度实时预测模拟方法和理论，及其在洪水、大气污染等自然灾害和环境问题中的应用。
邀请人：陈斌 副研究员 承办单位：水利水电学院
