Variational system identification of the partial differential equations governing microstructure evolution in materials: Inference over sparse and spatially unrelated data-Reference-Cited by-同舟云学术

Variational system identification of the partial differential equations governing microstructure evolution in materials: Inference over sparse and spatially unrelated data

Published:2021-04 Issue: Volume:377 Page:113706
ISSN:0045-7825
Container-title:Computer Methods in Applied Mechanics and Engineering
language:en
Short-container-title:Computer Methods in Applied Mechanics and Engineering

Author:

Wang Z.,Huan X.,Garikipati K.

Funder

Defense Advanced Research Projects Agency

Toyota Research Institute

Publisher

Elsevier BV

Subject

Computer Science Applications,General Physics and Astronomy,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Reference45 articles.

1. Multi-physics simulations of lithiation-induced stress in litio electrode particles;Jiang;J. Phys. Chem. C,2016

2. Mechano-chemical spinodal decomposition: A phenomenological theory of phase transformations in multi-component crystalline solids;Rudraraju;Nat. Comput. Mater.,2016

3. A variational treatment of material configurations with application to interface motion and microstructural evolution;Teichert;J. Mech. Phys. Solids,2017

4. Free energy of a nonuniform system. i interfacial energy;Cahn;J. Chem. Phys.,1958

5. The chemical basis of morphogenesis;Turing;Phil. Trans. R. Soc. Lond. Ser. B,1952

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity;International Journal for Numerical Methods in Engineering;2024-07-04

2. Coarse-graining Hamiltonian systems using WSINDy;Scientific Reports;2024-06-24

3. Integrating inverse reinforcement learning into data-driven mechanistic computational models: a novel paradigm to decode cancer cell heterogeneity;Frontiers in Systems Biology;2024-03-08

4. Pattern formation in dense populations studied by inference of nonlinear diffusion‐reaction mechanisms;International Journal for Numerical Methods in Engineering;2024-03-06

5. Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics;Communications Physics;2024-01-13