System Identification of Spatial Distribution of Structural Parameters Using Modified Transitional Markov Chain Monte Carlo Method
Publication: Journal of Engineering Mechanics
Volume 143, Issue 9
Abstract
Uncertain changes in spatial distribution of structural parameters, caused by deterioration or damage, may weaken the structure and result in unexpected losses of properties or casualties. In recent decades, to identify spatial distribution of parameters, various system identification (SI) methods have been developed based on optimization algorithms employing various regularization techniques. However, such optimization-based SI methods may suffer from ill-posedness of the optimization problem under uncertain measurement noises. Moreover, depending on boundary and traction conditions, the accuracy and robustness of SI methods may differ. In this paper, to overcome these technical challenges in identification of spatial distribution, a new SI method is developed by modifying the transitional Markov chain Monte Carlo (m-TMCMC). In addition to the modifications introduced to the sampling algorithm, the proposed method enhances robustness of the SI results by exploiting the results by the maximum likelihood estimation and finite-element updating. To identify general shapes of spatial distribution with a reasonable number of parameters, a spatial deterioration model is proposed based on the modes obtained based on a random field model called Karhunen–Loeve expansion. The proposed SI method is tested and demonstrated through numerical examples of steel plate and B-pillar structure, in which the effects of random measurement errors are also considered. The numerical examples demonstrate accuracy and robustness of the proposed method.
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Acknowledgments
The research was supported by the Institute of Construction and Environmental Engineering at Seoul National University, and the project “Development of Lifecycle Engineering Technique and Construction Method for Global Competitiveness Upgrade of Cable Bridges,” funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of the Korean Government, and National Research Foundation of Korea (NRF)—Deutsche Forschungsgemeinschaft (DFG) Collaborative Reasearch Programme Grant (No. 0583-20150071). This support is gratefully acknowledged. Any opinions, findings, and conclusions expressed in this paper are those of the authors, and do not necessarily reflect the views of the sponsors.
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Published In
Journal of Engineering Mechanics
Volume 143 • Issue 9 • September 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Dec 19, 2016
Accepted: Mar 21, 2017
Published online: Jun 29, 2017
Published in print: Sep 1, 2017
Discussion open until: Nov 29, 2017
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