Weak Form Theory-guided Neural Network (TgNN-wf) for Deep Learning of Subsurface Single and Two-phase Flow

no code implementations • 8 Sep 2020 • Rui Xu, Dongxiao Zhang, Miao Rong, Nanzhe Wang

In the weak form, high order derivatives in the PDE can be transferred to the test functions by performing integration-by-parts, which reduces computational error.

A Lagrangian Dual-based Theory-guided Deep Neural Network

no code implementations • 24 Aug 2020 • Miao Rong, Dongxiao Zhang, Nanzhe Wang

In this paper, the Lagrangian dual-based TgNN (TgNN-LD) is proposed to improve the effectiveness of TgNN.