An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications

1 code implementation • 27 Aug 2019 • Esteban Samaniego, Cosmin Anitescu, Somdatta Goswami, Vien Minh Nguyen-Thanh, Hongwei Guo, Khader Hamdia, Timon Rabczuk, Xiaoying Zhuang

In this contribution, we explore Deep Neural Networks (DNNs) as an option for approximation.

Transfer learning enhanced physics informed neural network for phase-field modeling of fracture

no code implementations • 4 Jul 2019 • Somdatta Goswami, Cosmin Anitescu, Souvik Chakraborty, Timon Rabczuk

While most of the PINN algorithms available in the literature minimize the residual of the governing partial differential equation, the proposed approach takes a different path by minimizing the variational energy of the system.

Numerical Integration Transfer Learning