Iris Tien

Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network

Tien, I., Pozzi, M., and Der Kiureghian, A., “Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network,” In G. Deodatis, B. Ellingwood, and D. Frangopol, eds. Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures, New York: CRC Press, pp. 2481-2488, June 2013

Click for full text of paper (pdf): Tien et al, Inference on Maximum Structural Response Based on Measured Accelerations Using Dynamic Bayesian Network

Abstract — A dynamic Bayesian network (DBN) is a useful tool for analyzing uncertain systems that evolve with time. As such, it is useful in structural health monitoring applications where measurements can be noisy and uncertain. We propose an algorithm that uses a DBN formulation of the system to assess the maximum response of a structure under seismic load, given recordings from accelerometers placed on the structure. By investigating the impact on the accuracy of the sensor characteristics, including the number of sensors, their positions within the structure, and the precision of their measurements, the results of our analysis inform decision making on the use of accelerometers in the monitoring of structures under seismic loads. We assume linear Gaussian response, which is appropriate for serviceability studies. An example application demonstrates that the DBN is a powerful tool for processing of information gained from monitoring devices.