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Modified Hamiltonian Monte Carlo‐based Bayesian finite element model updating of steel truss bridge
Author(s) -
Baisthakur Shubham,
Chakraborty Arunasis
Publication year - 2020
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2556
Subject(s) - markov chain monte carlo , finite element method , truss , monte carlo method , hybrid monte carlo , algorithm , computer science , mathematical optimization , bayesian probability , mathematics , structural engineering , engineering , artificial intelligence , statistics
Summary The aim of this study is to develop a Hamiltonian Monte Carlo‐based algorithm for finite element model updating in the Bayesian framework. The proposed algorithm uses adaptive prior‐based approach, which helps to generate the intermediate pdf s. Numerical analysis is carried out with different coefficient of variations of the prior for model updating. Guidelines for their proper selection procedure are also prescribed in this work. The efficiency of the proposed method is demonstrated using synthetic experiments and actual test data for updating the finite element model of a steel truss bridge. Finally, performance of this algorithm is compared with the standard Markov chain Monte Carlo algorithm to demonstrate its advantages.