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必威、所2021年系列学术活动(第112场):Eric Li 讲师 Teesside University,英国

发表于: 2021-08-01   点击: 

报告题目:A data-driven smoothed meshfree method

报 告 人:Eric Li 讲师 Teesside University

报告时间:2021年7月31日 19.00-21:00

报告地点:腾讯会议 会议 ID:503 480 601

校内联系人:徐旭 xuxu@jlu.edu.cn


报告摘要:In this talk, I will introduce a new computing paradigm: data-driven smoothed meshfree method, where the data are directly from experimental material data and pertinent constraints and conservation laws. This method avoids the empirical modeling step of conventional computing. Data-driven solvers aim to find the state satisfying the conservation laws that is closest to the data set. The resulting data-driven problem thus consists of the minimization of a distance function to the data set in phase space subject to constraints introduced by the conservation laws. I investigate the performance of data-driven solvers by means of two examples of application, namely, the static equilibrium of nonlinear three-dimensional trusses and linear elasticity. I also illustrate the robustness of data-driven solvers with respect to spatial discretization.


报告人简介:Dr. Eric Li is a senior lecturer at Teesside University, and the associate editor/editor board for three SCI indexed journals. He is a Chartered Engineer, and achieved the status of Fellow of Higher Education Academy (FHEA) in 2020.  His research is focused on computational mechanics, artificial intelligence, biomechanics, topology optimization, acoustic analysis, and structural health monitoring (SHM).