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An Adaptive Substructure-Based Model Order Reduction Method for Nonlinear Seismic Analysis in OpenSees

Jian Wang1, 2, Ming Fang3, *, Hui Li1, 2

1 Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin, 150090, China.
2 Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin, 150090, China.
3 College of Shipbuilding Engineering, Harbin Engineering University, Harbin, 150001, China.

* Corresponding Author: Ming Fang. Email: email.

Computer Modeling in Engineering & Sciences 2020, 124(1), 79-106. https://doi.org/10.32604/cmes.2020.09470

Abstract

Structural components may enter an initial-elastic state, a plastic-hardening state and a residual-elastic state during strong seismic excitations. In the residual-elastic state, structural components keep in an unloading/reloading stage that is dominated by a tangent stiffness, thus structural components remain residual deformations but behave in an elastic manner. It has a great potential to make model order reduction for such structural components using the tangent-stiffness-based vibration modes as a reduced order basis. In this paper, an adaptive substructure-based model order reduction method is developed to perform nonlinear seismic analysis for structures that have a priori unknown damage distribution. This method is able to generate time-varying substructures and make nonlinear model order reduction for substructures in the residual-elastic phase. The finite element program OpenSees has been extended to provide the adaptive substructure-based nonlinear seismic analysis. At the low level of OpenSees framework, a new abstract layer is created to represent the time-varying substructures and implement the modeling process of substructures. At the high level of OpenSees framework, a new transient analysis class is created to implement the solving process of substructure-based governing equations. Compared with the conventional time step integration method, the adaptive substructure-based model order reduction method can yield comparative results with a higher computational efficiency.

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APA Style
Wang, J., Fang, M., Li, H. (2020). An adaptive substructure-based model order reduction method for nonlinear seismic analysis in opensees. Computer Modeling in Engineering & Sciences, 124(1), 79-106. https://doi.org/10.32604/cmes.2020.09470
Vancouver Style
Wang J, Fang M, Li H. An adaptive substructure-based model order reduction method for nonlinear seismic analysis in opensees. Comput Model Eng Sci. 2020;124(1):79-106 https://doi.org/10.32604/cmes.2020.09470
IEEE Style
J. Wang, M. Fang, and H. Li, “An Adaptive Substructure-Based Model Order Reduction Method for Nonlinear Seismic Analysis in OpenSees,” Comput. Model. Eng. Sci., vol. 124, no. 1, pp. 79-106, 2020. https://doi.org/10.32604/cmes.2020.09470

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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