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同济大学姜立建教授、关晓飞副教授网络学术报告

发布人:    发布时间:2021-11-22    【打印此页】

 

        报告题目:Data-driven modeling for nonlinear dynamic multiscale problems  

        报  告  人:姜立建

        工作单位:同济大学

        报告时间:2021-11-25  10:00-12:00

        腾讯会议ID: 945 493 907

     

        报告摘要:Multiscale phenomena significantly impact on the computation and modeling of scientific and engineering problems. In this talk, I will present the motivation and ideas for coarsening multiscale models.  Then a data-driven modeling is presented for nonlinear multiscale dynamic problems using Koopman operator learning.

        报告人简介:姜立建, 同济大学数学科学学院教授,博士毕业于美国得克萨斯农工大学,主要研究方向是多尺度问题的建模、计算及其不确定性量化。曾获国家青年人才项目支持, 在科学计算及其交叉学科一流期刊发表论文50余篇,现任Journal of Computational and Applied Mathematics,  Journal of Computational Mathematics and Data Science, 《数值计算与计算机应用》等科学期刊的编委。

 

        报告题目:Stochastic higher-order three-scale strength prediction models for composite structures with micromechanical analysis  

        报  告  人:关晓飞

        工作单位:同济大学

        报告时间:2021-11-25  10:00-12:00

        腾讯会议ID: 945 493 907

     

        报告摘要:Stochastic multiscale modeling and analysis for the strength prediction of composite structures with complex multiscale microstructures remains a challenging problem. This is mainly due to the fact that high-dimensional physical properties not only have multiscale non-linear features in physical space, but also need to obtain inherent low-dimensional representation in random space, which many repeated evaluations of the corresponding stochastic multiscale model are often required. In this paper, we develop a stochastic higher-order three-scale strength prediction models (SHTSPM) for composite structures, which is designed to overcome limitations of prohibitive computation involving the microscale, the mesoscale and the macroscale. By virtue of asymptotic homogenization theory and micromechanical analysis, the SHTSPM model is derived from the detailed stochastic high-order three-scale homogenization analysis implemented with analytic solutions of composite structures subjected to tensile, bending and twist loads. The SHTSPM models represent strength anisotropy through different strength criterions for evaluating the yield state of the different component materials of composite structures, which are induced by aggregate–matrix interface deboning or matrix cracking in multiple scales. Moreover, these are constructed and calibrated from the high-accuracy mechanical analysis with help of two classes of mesoscopic and microscopic auxiliary cell functions, which are obtained from the mesoscale and microscale microstructures, respectively. The corresponding numerical algorithm of SHTSPM based on finite element method (FEM) and a preprocessing strategy is designed to improve the computational efficiency. Finally, the numerical experiments in 3D cases illustrate the outstanding performance of the proposed SHTSPM models, and the proposed method can significantly reduce the computational time, and can be further extended to evaluate damage or fracture properties of composite structures.

        报告人简介:关晓飞,同济大学数学科学学院副教授,博士生导师,中国工业与应用数学学会不确定量化专委会常务委员,中国仿真学会不确定系统分析与仿真专业委员会委员,老员工创新创业导师,研究兴趣为数据驱动的多尺度多物理场耦合建模与深度学习。2009年博士毕业于中国科学院数学与系统科学研究院,2012年6月至2012年10月,在奥地利维也纳科技大学结构与力学系从事博士后研究,2013年12月至2015年1月在美国加州大学圣地亚哥分校数学系做访问学者,主持和参加多项国家级与部级科研项目,并在国际知名期刊上发表20多篇高水平的学术论文。

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