A Physics-Informed Neural Operator for the Simulation of Surface Waves

Author(s):Show less -

Mathias, Marlon S. ; Netto, Caio F. D. ; Moreno, Felipe M. ; Coelho, Jefferson F. ; de Freitas, Lucas P. ; de Barros, Marcel R. ; de Mello, Pedro C. ; Dottori, Marcelo ; Cozman, Fabio G. ; Costa, Anna H. R. ; Nogueira Junior, Alberto C. ; Gomi, Edson S. ; Tannuri, Eduardo A.

• Document type: Journal article
• Source: JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING-TRANSACTIONS OF THE ASME; v. 146, n. 6, p. 10-pg., 2024-12-01.

Abstract

We develop and implement a neural operator (NOp) to predict the evolution of waves on the surface of water. The NOp uses a graph neural network (GNN) to connect randomly sampled points on the water surface and exchange information between them to make the prediction. Our main contribution is adding physical knowledge to the implementation, which allows the model to be more general and able to be used in domains of different geometries with no retraining. Our implementation also takes advantage of the fact that the governing equations are independent of rotation and translation to make training easier. In this work, the model is trained with data from a single domain with fixed dimensions and evaluated in domains of different dimensions with little impact to performance. (AU)

• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 20/16746-5 - Physics-informed machine learning applied for forecasting metocean conditions
• Grantee: Felipe Marino Moreno
• Support Opportunities: Scholarships in Brazil - Doctorate