报告一：

 报告主题：Bayesian Model Updating and Uncertainty Quantification

 报告时间：2024年10月30日 上午9:00-10:30

 报告地点：A18-705

 内容介绍：This lecture introduces the Bayesian framework for model updating, which allows the systematic integration of experimental data with FE models. Uncertainty quantification plays a central role in this process, as it distinguishes between aleatory (inherent randomness) and epistemic (lack of knowledge) uncertainties. Bayesian updating uses prior knowledge and experimental data to update the probability distributions of model parameters. The lecture will cover the fundamentals of Bayesian inference, including Bayes' Theorem, likelihood functions, and Markov Chain Monte Carlo (MCMC) sampling. Practical applications of Bayesian updating will be demonstrated using benchmark test cases.

 报告二：

 报告主题：Advanced Bayesian Techniques and Case Studies

 报告时间：2024年10月30日 上午10:30-12:00

 报告地点：A18-705

 内容介绍：This lecture delves deeper into advanced Bayesian methods for model updating, focusing on practical applications in complex engineering systems. Special attention will be given to the Transitional MCMC (TMCMC) method, which efficiently handles high-dimensional and multimodal probability distributions. The lecture will also explore the use of distance-based likelihood functions for improved uncertainty quantification in both deterministic and stochastic model updating. Case studies, including an experimental 3-Degree of Freedom rig system and a stochastic airplane model challenge, will illustrate the power of Bayesian updating in handling real-world uncertainties.

主办单位：必威西汉姆官网平台、航空航天结构力学及控制全国重点实验室、校科协

报告人简介：

 毕司峰博士是英国南安普顿大学航空与航天系的助理教授。他于2015年在法国贝桑松的Femto-ST研究所从事博士后研究。随后他获得了德国亚历山大·冯·洪堡研究基金资助，于2017年在德国汉诺威莱布尼兹大学继续从事不确定性和可靠性方面的研究。毕博士的研究领域包括不确定性量化、随机模型更新、数值模型验证与确认，尤其专注于复杂航空航天工程动力学中的应用。他的研究特别关注使用高级蒙特卡罗模拟、近似贝叶斯计算和基于可靠性的优化等技术进行不精确和非概率分析。毕博士目前是ASCE-ASME Journal of Risk and Uncertainty的副主编，同时是美国航空航天学会（AIAA）的高级会员。