Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil

23 June 2023

Papers citing "Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil"

6 / 6 papers shown

Title
SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks Bruno Jacob Amanda A. Howard P. Stinis 45 6 0 09 Nov 2024
Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients Rahul Sundar Didier Lucor Sunetra Sarkar AI4CE 26 0 0 27 Feb 2024
Loss Landscape Engineering via Data Regulation on PINNs Vignesh Gopakumar Stanislas Pamela D. Samaddar PINN 38 16 0 16 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 75 40 0 16 May 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 116 354 0 05 Oct 2021
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 91 387 0 10 Mar 2020