@Article{cmes.2020.09470, AUTHOR = {Jian Wang, Ming Fang, Hui Li}, TITLE = {An Adaptive Substructure-Based Model Order Reduction Method for Nonlinear Seismic Analysis in OpenSees}, JOURNAL = {Computer Modeling in Engineering \& Sciences}, VOLUME = {124}, YEAR = {2020}, NUMBER = {1}, PAGES = {79--106}, URL = {http://www.techscience.com/CMES/v124n1/39383}, ISSN = {1526-1506}, 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.}, DOI = {10.32604/cmes.2020.09470} }