工程可靠性与随机力学国际联合研究中心

10周年庆典杰出讲座

(Distinguished Lectures for the 10th

Anniversary Celebration of JCERM)第01期

工程可靠性与随机力学国际联合研究中心

2026年第 1 期（总第117期）学术报告

工程力学研究中心第72期学术报告

文远讲坛346期

报告主题

TOPIC

强非线性和不确定性下的鲁棒性设计

Robust design under strong nonlinearities and uncertainties

报告人

SPEAKER

Prof. Michael Beer

Professor, Head of the Institute for Risk and Reliability, Leibniz 

Universität Hannover, Germany

ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems主编

ASCE Alfredo Ang Award获得者

报告时间

TIME

2026年3月18日（周三）下午15:30-16:30

报告地点

VENUE

同济大学土木大楼 A305

主持人

CHAIR

陈建兵教授、彭勇波教授

报告内容

Abstract

Common approaches for robust design rely on the condition that the underlying problem is reasonably well-behaved so that input-output dependencies can be described or be approximated with some functional dependencies, either in terms of physics or in terms of uncertainty characteristics. However, this condition does not hold when very strong nonlinearities and large uncertainties with unknown characteristics from mixed physical and numerical sources are involved in a dynamical problem. Such problems appear, for example, in crashworthiness design of car structures. To attack this class of problems, an approach based on pattern recognition in sampling results in combination with a worst-case analysis within potential design domain is presented. This approach concerns a generally applicable numerical procedure for designing robust structures, which can be coupled with any arbitrary nonlinear computational model. It delivers a number of alternative options for the final design, from which the preference solution can be identified through a discrete three-criteria decision problem. The goal of the resulting design is that the structural behavior is only marginally affected by uncertainty and by changes in the design parameters, which further provides comfortable decision margins to the decision-makers in the construction or production process. The proposed procedure is demonstrated by means of a numerical example and of an example from engineering practice in vehicle crashworthiness design.

报告人简介

Speaker Bio

Michael Beer is Professor and Head of the Institute for Risk and Reliability, Leibniz Universität Hannover, Germany. He is also part time Professor at the University of Liverpool and guest Professor at Tongji University and Beijing University of Science and Technology, China. He obtained a doctoral degree from Technical University Dresden, Germany, and worked for Rice University, National University of Singapore, and the University of Liverpool, UK. Dr. Beer’s research is focused on uncertainty quantification in engineering with emphasis on imprecise probabilities. Dr. Beer is Editor in Chief of the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A Civil Engineering and Part B Mechanical Engineering. He is also Editor in Chief (joint) of the Encyclopedia of Earthquake Engineering, Associate Editor of Mechanical Systems and Signal Processing as well as Information Sciences, and Editorial Board Member of Engineering Structures, Structural Safety, Computers and Structures, Probabilistic Engineering Mechanics and several other international journals. He has won several awards including the International Academic Contribution Award of the Chinese Society for Vibration Engineering 2024 and the Alfredo Ang Award on Risk Analysis and Management of Civil Infrastructure of ASCE 2022. Dr. Beer is the Chairman of the European Safety and Reliability Association (ESRA), President-elect of the International Association for Structural Safety and Reliability Association (IASSAR) for 2027-2031, and a Co-Chair of the Risk and Resilience Measurements Committee (RRMC), Infrastructure Resilience Division (IRD), ASCE. He is serving on the Executive Board of the European Association of Structural Dynamics (EASD), and on the Board of Directors of the International Association for Probabilistic Safety Assessment and Management (IAPSAM). He is a Fellow of the Alexander von Humboldt-Foundation and a Member of ASCE (EMI), ASME, CERRA, IACM and GACM.