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A dynamic Bayesian network framework for risk assessment of systems based on sensor measurements

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

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.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076250

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/