Hui Qin   

Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

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Language:English

Paper Publications

Title of Paper:Reduction of Coupling Interface Degrees of Freedom in Mixed-Interface Component Mode Synthesis

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Date of Publication:2020-02-01

Journal:APPLIED SCIENCES-BASEL

Included Journals:SCIE

Volume:10

Issue:8

Key Words:mixed-interface component mode synthesis (MCMS); finite element method (FEM); coupling interface degrees of freedom; interface nodal coordinate transformation; interpolating scheme

Abstract:A new coupling interface degrees of freedom (DOFs) reduction technique for the mixed-interface component mode synthesis (MCMS) method is proposed, which referred to as the MCMS-rid method. This approach employs a set of shape functions via the linear interpolation (LI) in finite element method (FEM) to realize interface nodal coordinate transformations for each substructure, and then only a small number of interpolation basic nodes (IBNs) will be involved in mode synthesis and the following dynamic analysis. Unlike the majority of available CMS methods that retain a full dimension of the coupling interface DOFs, the MCMS-rid method allows to reduce the coupling interface DOFs significantly and enhance the computational efficiency. Three numerical models, including a rectangular beam with two ends fixed, a non-rectangular beam with the button fixed and a simplified dam-foundation system with different material properties, are presented to demonstrate the computational accuracy and efficiency of the proposed method. The results indicate that favourable accuracy with a least number of retained DOFs involved in mode synthesis can be obtained for solving eigenvalue problems when compared with other MCMS methods. The optimal number and distribution of the IBNs are discussed on structural dynamic analysis as well. It is shown that the more the IBNs are involved in mode synthesis, the better the precision that will be received. Furthermore, when the sub-regions are nearly square, the precision is best.

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