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Proper orthogonal decomposition‐based model order reduction via radial basis functions for molecular dynamics systems
Author(s) -
Lee ChungHao,
Chen JiunShyan
Publication year - 2013
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.4552
Subject(s) - radial basis function , discretization , molecular dynamics , nonlinear system , basis function , transformation (genetics) , basis (linear algebra) , reduction (mathematics) , space (punctuation) , mathematics , statistical physics , physics , computational chemistry , mathematical analysis , chemistry , computer science , quantum mechanics , artificial neural network , geometry , biochemistry , machine learning , gene , operating system
SUMMARY Model order reduction for molecular dynamics (MD) systems exhibits intrinsic complexities because of the highly nonlinear and nonlocal multi‐atomic interactions in high dimensions. In the present work, we introduce a proper orthogonal decomposition‐based method in conjunction with the radial basis function (RBF) approximation of the nonlinear and nonlocal potential energies and inter‐atomic forces for MD systems. This approach avoids coordinate transformation between the physical and reduced‐order coordinates, and allows the potentials and inter‐atomic forces to be calculated directly in the reduced‐order space. The RBF‐approximated potential energies and inter‐atomic forces in the reduced‐order space are discretized on the basis of the Smolyak sparse grid algorithm to further enhance the effectiveness of the proposed method. The good approximation properties of RBFs in interpolating scattered data make them ideal candidates for the reduced‐order approximation of MD inter‐atomic force calculations. The proposed approach is validated by performing the reduced‐order simulations of DNA molecules under various external loadings. Copyright © 2013 John Wiley & Sons, Ltd.