Towards Fast Simulation of Environmental Fluid Mechanics with
Multi-Scale Graph Neural Networks

Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks

5 May 2022

Stathi Fotiadis

Anil A. Bharath

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Papers citing "Towards Fast Simulation of Environmental Fluid Mechanics with Multi-Scale Graph Neural Networks"

7 / 7 papers shown

Title
M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations Bo Lei Victor M. Castillo Yeping Hu AI4CE 52 0 0 12 Sep 2025
Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities Mohammad Ahangarkiasari Hassan Pouraria AI4CE 89 0 0 07 Sep 2025
A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components Haoran Li Yingxue Zhao Haosu Zhou Tobias Pfaff Nan Li 145 2 0 16 Mar 2025
Beyond Grid Data: Exploring Graph Neural Networks for Earth ObservationIEEE Geoscience and Remote Sensing Magazine (GRSM), 2024 Shan Zhao Zhaiyu Chen Zhitong Xiong Yilei Shi Sudipan Saha Xiao Xiang Zhu AI4CE 270 14 0 05 Nov 2024
Multiscale Neural Operators for Solving Time-Independent PDEs Winfried Ripken Lisa Coiffard Felix Pieper Sebastian Dziadzio AI4CE 128 3 0 10 Nov 2023
Multi-GPU Approach for Training of Graph ML Models on large CFD Meshes Sebastian Strönisch Maximilian Sander A. Knüpfer M. Meyer AI4CE 196 8 0 25 Jul 2023
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNInternational Conference on Machine Learning (ICML), 2022 Yadi Cao Menglei Chai Minchen Li Jian Ren AI4CE 298 36 0 05 Oct 2022