A framework for post-earthquake risk assessment and decision making for infrastructure systems is developed. Use is made of the Bayesian network methodology for modeling earthquake hazards and system performance, as well as for probabilistic updating in light of an evolving state of information gained from ground motion sensors and observations of the system component states. The Bayesian network is extended by addition of decision and utility nodes to construct an influence diagram, which is used for post-earthquake decision making regarding the type of inspection to perform or for setting the performance level of components. A value-of-information heuristic is used to determine the best sequence of component inspections. The methodology is demonstrated by its application to a hypothetical model of a segment of the California high-speed rail system.      «

A framework for post-earthquake risk assessment and decision making for infrastructure systems is developed. Use is made of the Bayesian network methodology for modeling earthquake hazards and system performance, as well as for probabilistic updating in light of an evolving state of information gained from ground motion sensors and observations of the system component states. The Bayesian network is extended by addition of decision and utility nodes to construct an influence diagram, which...     »