Bayesian Inference Based Uncertainty Quantification and Calibration of Numerical Models of Existing Structures

2013 Journal of Japan Society of Civil Engineers Ser A2 (Applied Mechanics (AM))  
博(工) 横浜国立大学准教授 都市イノベーション研究院(〒240-8501 神奈川県横浜市保土ヶ谷区常盤台 79-5) ** Ph.D. 東京大学教授 工学系研究科社会基盤学専攻(〒113-8656 東京都文京区本郷 7-3-1) This paper presents the Bayesian inference based model calibration strategy for constructing validated numerical models of the existing structures. There exist uncertain changes in the model parameters, such as material properties and boundary conditions, from the nominal condition due to deteriorations or possible damages in the existing structures. The target in this study was
more » ... e dynamic analysis model of an existing bridge, and the model calibration procedure was applied by using measured resonant frequencies as the comparative feature. It was then shown that the meaningful posterior distributions cannot be obtained without the appropriate prior distribution setting based on the engineering judgments. The numerical model was then successfully calibrated by using the meaningful posterior distributions.
doi:10.2208/jscejam.69.i_711 fatcat:lzmmxwzinffs5mpmb4pghyvlai