庆祝工程可靠性与随机力学国际联合研究中心

成立 10 周年杰出讲座

(Distinguished Lectures for the 10th

Anniversary Celebration of JCERSM) 第 5 期

工程可靠性与随机力学国际联合研究中心

2026 年第 9 期（总第 125 期）学术报告

工程力学研究中心第 80 期学术报告

文远讲坛 355 期

报告主题

TOPIC

复杂动力系统的不确定性量化与可靠性分析

Uncertainty quantification and reliability analysis for complex dynamical systems

报告人

SPEAKER

Prof. Matthias Faes

TU Dortmund University, Germany

报告时间

TIME

2026 年 7 月 1 日（周三）上午 10:00-11:00

报告地点

VENUE

同济大学土木大楼 A305

主持人

CHAIR

陈建兵 教授

联系人: 牛立志

报告内容

Abstract

Uncertainties are ubiquitous in the simulation of the structural dynamic behaviour of structures and machines, particularly when the effects of natural phenomena such as earthquakes or wind loads must be taken into account. Stochastic processes provide a rigorous framework for representing uncertainties and the associated space and time correlations of uncertain loads, grounded in the well-established principles of probability theory. Accounting for the stochastic nature of external loads, as well as for uncertainties inherent in the system itself, enables the approximation of structural failure probabilities through stochastic dynamic simulations. In practice, however, estimating the failure probability of complex dynamical systems typically relies on computationally intensive simulation models. Moreover, the presence of stochastic processes often leads to problem formulations involving hundreds or even thousands of random variables. Together, these aspects pose substantial challenges for the reliable simulation of realistic engineering systems.

In this talk, I will present practical numerical schemes that aim to address these challenges. The presentation will draw on recent work in the reliability analysis of stochastic dynamical systems, with a focus on advances in surrogate modelling, including functional dimensionality reduction and Bayesian active learning, as well as on efficient sampling strategies such as multi-domain line sampling and importance line sampling.

报告人简介

Speaker Bio

Matthias Faes became a full Professor in Reliability Engineering at TU Dortmund at the age of 30, since February 2022. Before, he was a post-doctoral fellow of the Research Foundation Flanders (FWO) working at the Department of Mechanical Engineering of KU Leuven and was also affiliated to the Institute for Risk and Reliability at the University of Hannover as an Alexander von Humboldt Fellow. He graduated summa cum laude as Master of Science in Engineering Technology in 2013 and obtained his PhD in Engineering Technology from KU Leuven in 2017. Since then, he works on theoretical and numerical methods to perform efficient uncertainty quantification and reliability analysis under scarce data and information, including inverse and data-driven methods, surrogate modeling schemes, stochastic fields and imprecise probabilities.

Matthias Faes is the winner of the 2017 ECCOMAS European PhD award for best PhD thesis in 2017 on computational methods in applied sciences and engineering in Europe, winner of the 2019 ISIPTA - IJAR Young Researcher Award for outstanding contributions to research on imprecise probabilities and winner of the 2023 EASD Junior Research Prize for his contribution to the development of methodologies for structural dynamics, and recently the 2026 ECCOMAS Olgierd Cecil Zienkiewicz Award among other national and international awards and honours. He is Associate Editor at Mechanical Systems and Signal Processing and Reliability Engineering and System Safety, as well as Associate Managing Editor of the ASCE-ASME Journal of Risk and Uncertainty in Engineering system parts A and B, and editorial board member of Nature Scientific Reports. On top, he serves on the excecutive boards of the European Association for Structural Dynamics (EASD), and the International Association for Reliability Engineering and Risk Management (IARERM. Finally, he is the chairman of the Committee on Probability and Statistics in the Physical Sciences of the Bernouilli Society, as well as Chairman of several technical committees of both the European Safety and Reliability Association (ESRA), as the International Association for Structural Satety and Reliability (IASSAR). Matthias Faes is author of more than 125 journal papers and more than 100 conference contributions and he has a Google Scholar H-index of 31 (3700+ citations) since 2016.