Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 142, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.106732
Keywords
Structural dynamics; Uncertainty quantification; Global sensitivity analysis; Arbitrary polynomial chaos expansion; Maximum entropy principle; Bridge structure
Categories
Funding
- National Key Research and Development Program of China [2017YFC0806100]
- National Natural Science Foundation of China [51878235, 51778204]
- Shenzhen Science and Technology program [KQTD20180412181337494]
Ask authors/readers for more resources
Uncertainty quantification (UQ) and global sensitivity analysis (GSA) of dynamic characteristics of complex systems subjected to uncertainty are jointly investigated in this paper. An efficient approach based on arbitrary polynomial chaos expansion (aPCE) is presented for analytical, unified implementation of UQ and GSA in structural dynamics. For UQ of dynamic characteristics, statistical moments and probability distributions of dynamic characteristics are analytically derived. Specifically, the aPCE is used to analytically calculate the statistical moments, and then the maximum entropy principle (MEP) is adopted to derive the closed-form expressions of the probability distributions using the obtained statistical moments. As an extension of UQ, GSA, which aims to assess the quantitative contributions of different structural parameters to the resultant variations of dynamic characteristics, is also analytically achieved by simply post-processing the aPCE coefficients. The present aPCE UQ and GSA method is highly computationally efficient for large-scale, complex structures, and it is also generally applicable independent of parameter distributions. The proposed aPCE-based approach for UQ and GSA is validated through a numerical truss bridge by the brute-force Monte Carlo simulation (MCS), and then is applied to a long-span steel arch bridge. (C) 2020 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available