Adjoint design sensitivity analysis of reduced atomic systems using generalized Langevin equation for lattice structures
Journal Article
·
· Journal of Computational Physics
- National Creative Research Initiatives Center for Isogeometric Optimal Design and Department of Naval Architecture and Ocean Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744 (Korea, Republic of)
An efficient adjoint design sensitivity analysis method is developed for reduced atomic systems. A reduced atomic system and the adjoint system are constructed in a locally confined region, utilizing generalized Langevin equation (GLE) for periodic lattice structures. Due to the translational symmetry of lattice structures, the size of time history kernel function that accounts for the boundary effects of the reduced atomic systems could be reduced to a single atom’s degrees of freedom. For the problems of highly nonlinear design variables, the finite difference method is impractical for its inefficiency and inaccuracy. However, the adjoint method is very efficient regardless of the number of design variables since one additional time integration is required for the adjoint GLE. Through numerical examples, the derived adjoint sensitivity turns out to be accurate and efficient through the comparison with finite difference sensitivity.
- OSTI ID:
- 22233570
- Journal Information:
- Journal of Computational Physics, Journal Name: Journal of Computational Physics Vol. 240; ISSN 0021-9991; ISSN JCTPAH
- Country of Publication:
- United States
- Language:
- English
Similar Records
Uncertainty quantification for generalized Langevin dynamics
Data-driven parameterization of the generalized Langevin equation
Data-driven molecular modeling with the generalized Langevin equation
Journal Article
·
Tue Dec 13 19:00:00 EST 2016
· Journal of Chemical Physics
·
OSTI ID:1465368
Data-driven parameterization of the generalized Langevin equation
Journal Article
·
Mon Nov 28 19:00:00 EST 2016
· Proceedings of the National Academy of Sciences of the United States of America
·
OSTI ID:1333885
Data-driven molecular modeling with the generalized Langevin equation
Journal Article
·
Thu Oct 01 00:00:00 EDT 2020
· Journal of Computational Physics
·
OSTI ID:1639916