Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures

1 code implementation • 16 Jul 2022 • Zhilu Lai, Wei Liu, Xudong Jian, Kiran Bacsa, Limin Sun, Eleni Chatzi

In the scope of physics-informed machine learning, this paper proposes a framework -- termed Neural Modal ODEs -- to integrate physics-based modeling with deep learning for modeling the dynamics of monitored and high-dimensional engineered systems.

Physics-informed machine learning