Summary of Neurosem: a Hybrid Framework For Simulating Multiphysics Problems by Coupling Pinns and Spectral Elements, By Khemraj Shukla et al.
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements
by Khemraj Shukla, Zongren Zou, Chi Hin Chan, Additi Pandey, Zhicheng Wang, George Em Karniadakis
First submitted to arxiv on: 30 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Fluid Dynamics (physics.flu-dyn)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel machine learning framework called NeuroSEM combines physics-informed neural networks (PINNs) with the high-fidelity Spectral Element Method (SEM) solver Nektar++ to tackle challenging multiphysics problems. The approach integrates PINNs’ data assimilation capabilities with SEM’s accuracy in solving partial differential equations (PDEs). This hybrid framework is demonstrated for thermal convection in cavity flow and flow past a cylinder, as well as for Rayleigh-Bénard convection with missing boundary conditions and noisy datasets. The authors also apply NeuroSEM to real particle image velocimetry (PIV) data to capture complex flow patterns. This approach offers improved accuracy and efficiency, making it suitable for tackling various engineering challenges. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary NeuroSEM is a new way to solve very hard math problems that involve many different types of physics. These problems are hard because they have lots of different variables that interact with each other in complicated ways. A special type of artificial intelligence called neural networks can help solve these problems, but they need to be trained on the right kind of data. NeuroSEM combines two powerful tools: a neural network and a super-accurate math solver called Spectral Element Method (SEM). This combination lets NeuroSEM solve complex math problems much faster and more accurately than either tool could do alone. The authors tested NeuroSEM by using it to solve some very hard math problems, and it worked really well. |
Keywords
» Artificial intelligence » Machine learning » Neural network
