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

• NISHIO Mayuko

  横浜国立大学　都市イノベーション研究院

• FUJINO Yozo

  東京大学　工学系研究科社会基盤学専攻

Bibliographic Information

Other Title

• ベイズ推定による既存構造物数値モデルの不確定性定量化とキャリブレーション

Abstract

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 the 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 modelwas then successfully calibrated by using themeaningful posterior distributions.

Journal

• Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM))

  Journal of Japan Society of Civil Engineers, Ser. A2 (Applied Mechanics (AM)) 69 (2), I_711-I_718, 2013

  Japan Society of Civil Engineers

Keywords

• Model validation
• uncertainty
• Bayesian inference
• existing structures

Details

• CRID: 1390282680326955904
• NII Article ID: 130004557403
• DOI: 10.2208/jscejam.69.i_711
• ISSN: 21854661
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed