Using physical energy as the loss function lets a deep neural network solve a range of computational mechanics PDEs, from linear elasticity to fourth-order plate bending, without meshes or data.
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An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications
Using physical energy as the loss function lets a deep neural network solve a range of computational mechanics PDEs, from linear elasticity to fourth-order plate bending, without meshes or data.