Phase-field DeepONet: physics-informed deep operator neural network for fast simulations of pattern formation governed by gradient flows of free-energy functionals
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Publication:6084433
DOI10.1016/j.cma.2023.116299arXiv2302.13368OpenAlexW4385772954MaRDI QIDQ6084433
Juner Zhu, Martin Z. Bazant, Wei Li
Publication date: 6 November 2023
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2302.13368
phase-field methodminimizing movement schemephysics-informed machine learningAllen-Cahn and Cahn-Hilliard equationsdeep operator neural network
Artificial neural networks and deep learning (68T07) Nonlinear parabolic equations (35K55) Spectral, collocation and related methods for initial value and initial-boundary value problems involving PDEs (65M70)
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