Iris Tien

A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements

Tien, I., Pozzi, M., and Der Kiureghian, A., “A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements,” In T. Haukaas, ed., Proceedings of the 12^th International Conference on Applications of Statistics and Probability in Civil Engineering, Vancouver, Canada, July 12-15, 2015

Click for full text of paper (pdf): Tien et al, A Dynamic Bayesian Network Framework for Risk Assessment of Systems Based on Sensor Measurements

Abstract — In this paper, a framework based the dynamic Bayesian network (DBN) is proposed to dynamically monitor the response of structures to hazards. The methodology enables the probabilistic analysis of the response of a system to a hazard that is stochastic, e.g., an earthquake ground motion, as it dynamically evolves in time, based on sensor measurements that are uncertain. The developed DBN framework is applied to the estimation of the inter-story drift of a multi-story shear-type building under earthquake hazard based on accelerometer measurements. Using a simulation approach, the ability of the method to accurately assess the system response is shown. In addition, robustness of the method to system uncertainties, including uncertainties in the structural characteristics, is demonstrated.