Multilevel Decomposition Framework for Reliability Assessment of Assembled Stochastic Linear Structural Systems
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7, Issue 1
Abstract
To reduce the computational cost of assembled stochastic linear structural dynamic systems, a three-staged reduced order model-based framework for forward uncertainty propagation was developed. First, the physical domain was decomposed by constructing an equivalent reduced order numerical model that limited the cost of a single deterministic simulation. This was done in two phases: (1) reducing the system matrices of the subcomponents using component mode synthesis and (2) solving the resulting reduced system with the help of domain decomposition in an efficient manner. Second, functional decomposition was carried out in the stochastic space by employing a multioutput machine learning model that reduced the number of eigenvalue analyses to be performed. Thus, a multilevel framework was developed that propagated the dynamic response from the subcomponent level to the assembled global system level efficiently. Subsequently, reliability analysis was performed to assess the safety level and failure probability of linear stochastic dynamic systems. The results achieved by solving a two-dimensional (2D) building frame and a three-dimensional (3D) transmission tower model illustrated good performance of the proposed methodology, highlighting its potential for complex problems.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Specifically, (1) the MATLAB data files in (.mat) format for both examples and (2) the geometric details of the second example in Gmsh will be available.
Acknowledgments
The authors gratefully acknowledge the support of the Engineering and Physical Sciences Research Council through the award of a program grant, “Digital Twins for Improved Dynamic Design,” Grant No. EP/R006768.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 7 • Issue 1 • March 2021
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© 2021 American Society of Civil Engineers.
History
Received: Jun 24, 2020
Accepted: Nov 5, 2020
Published online: Jan 12, 2021
Published in print: Mar 1, 2021
Discussion open until: Jun 12, 2021
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