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 JCERSM) 第 3 期

工程可靠性与随机力学国际联合研究中心

2026 年第 6 期（总第 122 期）学术报告

工程力学研究中心第 77 期学术报告

文远讲坛 351 期

报告主题

TOPIC

复杂供水管网水力性能评估的随机框架

A stochastic framework for hydraulic performance assessment
of complex water distribution networks

报告人

SPEAKER

Prof. Hector Jensen

智利费德里科圣玛利亚理工大学教授科技部高端外国专家

报告时间

TIME

2026年6月17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

This lecture discusses the assessment of the hydraulic performance of large-scale water distribution networks in the presence of uncertainty. The focus is on hydraulic reliability and leakage detection within the network. To this end, it is first observed that complex networks can be viewed as the structural skeletons of complex dynamical systems. Therefore, various techniques from stochastic dynamics can be adapted for the efficient estimation of network performance. The estimation of network reliability is performed using an efficient Markov chain Monte Carlo method, namely Hamiltonian Monte Carlo–based subset simulation. In this context, nodal demands, nodal heads, and pipe coefficients are modelled as uncertain parameters with different levels of variability. Failure is assumed to occur when the head at any node falls below a minimum allowable value. The effectiveness and practicality of the proposed method are demonstrated using a real, large-scale water distribution network. Within the stochastic framework, various analyses can be performed, including uncertainty propagation, reliability and reliability-sensitivity analysis, failure analysis, redundancy analysis, and robustness analysis. In addition, a Bayesian system identification methodology is proposed for leakage detection. In particular, an approach based on the structural reliability method is adopted. A model class selection analysis is used to identify leak locations and intensities. The methodology properly accounts for unavoidable uncertainties in measurements and modelling errors. The results of these analyses provide valuable insights into network performance and may assist utility managers in making informed decisions on a range of related issues. The stochastic framework can be extended to address other important problems, including contaminant source identification and network connectivity. Finally, owing to its generality, the proposed framework can, in principle, be applied to other critical utility networks such as electricity, gas, oil, and general pressurized systems.

报告人简介

Speaker Bio

Hector Jensen is a Professor Civil Engineering at the Santa Maria Technical University, Valparaiso, Chile, and Professor of Mechanical Engineering at the Catholic University of Chile, Santiago. Chile. He is a Mathematician Civil Engineer from the University of Chile, and he received his PhD in Applied Mechanics from the California Institute of Technology (CALTECH), Pasadena, USA. His research interests include Computational Stochastic Mechanics, Advanced Simulation Methods, Robust and Reliability-Based Optimization, Risk and Sensitivity Analysis, Fuzzy Analysis, Finite Element Analysis, Dynamic Sub-structuring, and Bayesian Model Updating. He has been visiting professor in several American and European universities, including University of California at Los Angeles (UCLA), California Institute of Technology (CALTECH), University of Michigan (UM), University of Innsbruck, etc. He has published numerous journal and conference papers, as well as book chapters in areas of his expertise. In addition, a book that deals with the application of reduced-order models to complex simulation-based problems has been published by Springer in 2019 (Sub-Structure Coupling for Dynamic Analysis: Application to Complex Simulation-Based Problems Involving Uncertainty). He is preparing a new book related to the Reliability, Sensitivity and Optimization of Linear Structural Systems under Stochastic Gaussian Excitation based on Advanced Simulation Techniques (to appear in the Springer book series Computational Methods in Engineering & Science). He has been invited to give lectures, keynotes, semi-plenary and plenary lectures in a number of universities and international conferences. He is member of the editorial board of several journals, and he has been guest editor of different Journals, including Computers and Structures, Mechanical Systems and Signal Processing and Reliability Engineering and System Safety. He is also member of the scientific committee of many international conferences and reviewer of different journals. In 2018 he was selected by the Recruitment Program of High-end Foreign Experts of the State Administration of Foreign Affairs of the People’s Republic of China. He is listed among the top 2% scientists globally by the Stanford/Elsevier ranking list in Civil Engineering and Applied Mathematics.