@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}
}