David Lehký研究员、Ondřej Slowik博士学术报告通知
地点：河海大学江宁校区乐学楼1116（南京市江宁区佛城西路8号）
时间：2016年6月2日（周四）下午2:30-5:00
主办单位：河海大学力学与材料学院、江苏省力学学会学术工作委员会
报告题目一：Inverse analysis for structural parameters using soft computing
报告人：David Lehký 研究员，捷克布尔诺科技大学
报告摘要：The lecture will focus on utilization of soft computing methods for solving inverse problems in civil and structural engineering. In the proposed method instead of finding the original inverse function in analytical form a surrogate model in the form of artificial neural network is utilized. Its main advantages are robustness, extensibility and ability to adapt to new conditions. Important part of the inverse method is the utilization of efficient small-sample simulation technique Latin Hypercube Sampling used for preparation of training set utilized in stochastic training of neural network. Two particular inverse problems will be discussed – (i) identification of fracture–mechanical parameters and (ii) inverse reliability problem. In case of material parameters identification, the aim is to obtain the set of selected fracture–mechanical parameters describing quasi-brittle behavior of concrete including crack initiation and propagation. The known response is represented by diagram load vs. deflection or load vs. crack mouth opening displacement recorded during testing of specimen. The functional relationship between material parameters and above mentioned response is given in the form of nonlinear finite element model of the specimen. The second inverse problem is an inverse reliability analysis, which belongs to the category of a structural design, i.e. identification of design parameters in order to satisfy desired reliability described by reliability indicators related to particular limit states. Here, parameters to be identified are deterministic or random design parameters related to structure itself, acting load or surrounding environment. Known (in this case desired) response is the safety level described by reliability indicators. Practical examples of both classes of inverse problems will be presented.
报告人简介： Dipl. Ing. David Lehký, Ph.D. is the research fellow at Brno University of Technology, Faculty of Civil Engineering. Among his research interests belong utilization of soft computing methods for inverse analysis, structural safety and reliability, stochastic computational mechanics and fracture mechanics of quasi-brittle materials. Since year 2004 he is actively involved in cooperation with BOKU University in Vienna, Austria, since 2012 he works there as a visiting lecturer). He is a member of Scientific Committee of the International Association on Life-Cycle Civil Engineering (IALCCE) and fib commission 2 – Safety and performance concepts.
报告题目二：Reliability-based optimization in structural engineering
报告人：Ondřej Slowik 博士，捷克布尔诺科技大学
报告摘要：Lecture will focus on the specific approach to reliability – based design optimization. It is based on double loop framework where the outer loop of algorithm covers the optimization part of process of reliability - based optimization and reliability constrains are calculated in inner loop. Innovation of suggested approach is in application of newly developed optimization strategy based on multilevel simulation using an advanced Latin Hypercube Sampling technique. This method is called Aimed multilevel sampling and it is designated for optimization of problems where only limited number of simulations is possible to perform due to enormous computational demands.
报告人简介：Dipl. Ing. Ondřej Slowik is the research assistant and Ph.D. student at Brno University of Technology Faculty of Civil Engineering. His field of focus is reliability – based structural optimization. Since year 2014 is actively involved in cooperation with BOKU University, Austria and companny Franz Oberndorfer GmbH & Co KG at nonlinear deterministic and stochastic modelling of precast prestressed girders.
时间：2016年6月2日（周四）下午2:30-5:00
主办单位：河海大学力学与材料学院、江苏省力学学会学术工作委员会
报告题目一：Inverse analysis for structural parameters using soft computing
报告人：David Lehký 研究员，捷克布尔诺科技大学
报告摘要：The lecture will focus on utilization of soft computing methods for solving inverse problems in civil and structural engineering. In the proposed method instead of finding the original inverse function in analytical form a surrogate model in the form of artificial neural network is utilized. Its main advantages are robustness, extensibility and ability to adapt to new conditions. Important part of the inverse method is the utilization of efficient small-sample simulation technique Latin Hypercube Sampling used for preparation of training set utilized in stochastic training of neural network. Two particular inverse problems will be discussed – (i) identification of fracture–mechanical parameters and (ii) inverse reliability problem. In case of material parameters identification, the aim is to obtain the set of selected fracture–mechanical parameters describing quasi-brittle behavior of concrete including crack initiation and propagation. The known response is represented by diagram load vs. deflection or load vs. crack mouth opening displacement recorded during testing of specimen. The functional relationship between material parameters and above mentioned response is given in the form of nonlinear finite element model of the specimen. The second inverse problem is an inverse reliability analysis, which belongs to the category of a structural design, i.e. identification of design parameters in order to satisfy desired reliability described by reliability indicators related to particular limit states. Here, parameters to be identified are deterministic or random design parameters related to structure itself, acting load or surrounding environment. Known (in this case desired) response is the safety level described by reliability indicators. Practical examples of both classes of inverse problems will be presented.
报告人简介： Dipl. Ing. David Lehký, Ph.D. is the research fellow at Brno University of Technology, Faculty of Civil Engineering. Among his research interests belong utilization of soft computing methods for inverse analysis, structural safety and reliability, stochastic computational mechanics and fracture mechanics of quasi-brittle materials. Since year 2004 he is actively involved in cooperation with BOKU University in Vienna, Austria, since 2012 he works there as a visiting lecturer). He is a member of Scientific Committee of the International Association on Life-Cycle Civil Engineering (IALCCE) and fib commission 2 – Safety and performance concepts.
报告题目二：Reliability-based optimization in structural engineering
报告人：Ondřej Slowik 博士，捷克布尔诺科技大学
报告摘要：Lecture will focus on the specific approach to reliability – based design optimization. It is based on double loop framework where the outer loop of algorithm covers the optimization part of process of reliability - based optimization and reliability constrains are calculated in inner loop. Innovation of suggested approach is in application of newly developed optimization strategy based on multilevel simulation using an advanced Latin Hypercube Sampling technique. This method is called Aimed multilevel sampling and it is designated for optimization of problems where only limited number of simulations is possible to perform due to enormous computational demands.
报告人简介：Dipl. Ing. Ondřej Slowik is the research assistant and Ph.D. student at Brno University of Technology Faculty of Civil Engineering. His field of focus is reliability – based structural optimization. Since year 2014 is actively involved in cooperation with BOKU University, Austria and companny Franz Oberndorfer GmbH & Co KG at nonlinear deterministic and stochastic modelling of precast prestressed girders.
(作者：邬萱 )