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Error estimation for the automated multi‐level substructuring method
Author(s) -
Boo SeungHwan,
Kim JinGyun,
Lee PhillSeung
Publication year - 2015
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.5161
Subject(s) - transformation (genetics) , computer science , eigenvalues and eigenvectors , residual , matrix (chemical analysis) , finite element method , algorithm , reliability (semiconductor) , transformation matrix , estimation , mathematical optimization , mathematics , engineering , biochemistry , chemistry , physics , materials science , power (physics) , structural engineering , kinematics , quantum mechanics , classical mechanics , systems engineering , composite material , gene
Summary In this study, we propose an effective method to estimate the reliability of finite element models reduced by the automated multi‐level substructuring (AMLS) method. The proposed error estimation method can accurately predict relative eigenvalue errors in reduced finite element models. A new, enhanced transformation matrix for the AMLS method is derived from the original transformation matrix by properly considering the contribution of residual substructural modes. The enhanced transformation matrix is an important prerequisite to develop the error estimation method. Adopting the basic concept of the error estimation method recently developed for the Craig–Bampton method, an error estimation method is developed for the AMLS method. Through various numerical examples, we demonstrate the accuracy of the proposed error estimation method and explore its computational efficiency. Copyright © 2015 John Wiley & Sons, Ltd.