Graph neural networks for laminar flow prediction around random two-dimensional shapes-Reference-Cited by-同舟云学术

Graph neural networks for laminar flow prediction around random two-dimensional shapes

Published:2021-12 Issue:12 Volume:33 Page:123607
ISSN:1070-6631
Container-title:Physics of Fluids
language:en
Short-container-title:Physics of Fluids

Author:

Chen J.¹,Hachem E.¹,Viquerat J.¹^ORCID

Affiliation:

1. MINES ParisTech, CEMEF PSL—Research University, 06904 Sophia, Antipolis, France

Publisher

AIP Publishing

Subject

Condensed Matter Physics,Fluid Flow and Transfer Processes,Mechanics of Materials,Computational Mechanics,Mechanical Engineering

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0064108

Reference40 articles.

1. Convolutional Neural Networks for Steady Flow Approximation

2. Prediction model of velocity field around circular cylinder over various Reynolds numbers by fusion convolutional neural networks based on pressure on the cylinder

3. Data-driven prediction of unsteady flow over a circular cylinder using deep learning

4. J. Chen , J. Viquerat , F. Heymes , and E. Hachem , “ A twin-decoder structure for incompressible laminar flow reconstruction with uncertainty estimation around 2D obstacles,” arXiv:2104.03619 [physics.flu-dyn] (2021).

5. Deep Learning Methods for Reynolds-Averaged Navier–Stokes Simulations of Airfoil Flows

Cited by 42 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. On the choice of physical constraints in artificial neural networks for predicting flow fields;Future Generation Computer Systems;2024-12

2. Rapid prediction for the transient dispersion of leaked airborne pollutant in urban environment based on graph neural networks;Journal of Hazardous Materials;2024-10

3. A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators;Scientific Reports;2024-08-06

4. Numerical simulation of wave-floater interactions using ISPH_GNN trained on data for wave-only cases;Ocean Engineering;2024-08

5. A hybrid method combining ISPH with graph neural network for simulating free-surface flows;Computer Physics Communications;2024-08