Towards a Risk-Based Design Paradigm for Structural Health Monitoring Systems
Abstract »The design of a structural health monitoring (SHM) systems must synthesize elements of performance, cost, and constraint, but no integrated design paradigm exists yet. This paper discusses these elements required for successful SHM development and deployment and proposes a framework rooted in Bayes risk from which design (and performance evaluation comparison) is possible. Optimal design or retrofit is achieved through minimizing overall risk subject to constraints.
Biography: Prof. Todd received his B.S.E (1992), M.S. (1993) and Ph.D. (1996) from Duke University Dept. of Mechanical Engineering and Materials Science. His research focuses on all aspects of SHM technology, including fiber optic sensor development, time series modeling, data-to-decision analytics/models, data mining, uncertainty quantification, and nonlinear dynamics. Homepage
Affiliation: University of California San Diego Structural Engineering 92093 La Jolla USA