Events Calendar

A Bayesian Network Framework for Seismic Infrastructure Risk Assessment & Decision Support

Title: Speaker: Michelle T. Bensi, Ph.D. Candidate, University of California, BerkeleyAbstract:A Bayesian network (BN) is a probabilistic graphical model that represents a set of random variables and their probabilistic dependencies. The variables may represent demand or capacity values, or the states of components and systems. BNs are graphical and intuitive, facilitate information updating, can be used for identification of critical components within a system, and can be extended by decision and utility nodes to solve decision problems. In particular, the facility for information updating renders the BN an ideal tool for infrastructure risk assessment and decision support. Evidence on one or more variables (e.g. observed component capacities, demands, or states) can be entered into the BN and this information propagates throughout the network to provide an up-to-date probabilistic characterization of the performance of an infrastructure system under an evolving state of information.This presentation will begin with a brief introduction to BNs. Next, a broad overview of a BN framework for infrastructure seismic risk assessment and decision support will be presented. Components of the framework include: (1) a seismic demand model of ground motion intensity as a spatially distributed Gaussian random field accounting for finite fault rupture and directivity effects, (2) models of component performance, (3) models of system performance, and (4) the extension of the BN to include decision and utility nodes to aid post-earthquake decision-making. Like all computational methods, BNs have limitations. In particular, calculations in BNs can be highly demanding of computer memory. A discussion of work done to address this limitation will be presented. An illustrative example will demonstrate the main ideas and approach. The presentation will conclude with a broader discussion of the use of BNs for modeling hazards, processing information, and aiding decision making with the goal of improving infrastructure system performance and reliability

Location: Kaprielian Hall (KAP) - 209

Audiences: Everyone Is Invited

Contact: Evangeline Reyes