Solving nonlinear subsonic compressible flow in infinite domain via multi-stage neural networks
Fuente:
arXiv
Saved in:
| Main Authors: | Qian, Xuehui, Tao, Hongkai, Wang, Yongji |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
by: Qian, Yixiao, et al.
Published: (2026)
by: Qian, Yixiao, et al.
Published: (2026)
Physics-informed neural networks for hidden boundary detection and flow field reconstruction
by: Zhu, Yongzheng, et al.
Published: (2025)
by: Zhu, Yongzheng, et al.
Published: (2025)
Efficient temporal prediction of compressible flows in irregular domains using Fourier neural operators
by: Nie, Yifan, et al.
Published: (2026)
by: Nie, Yifan, et al.
Published: (2026)
A Novel Paradigm in Solving Multiscale Problems
by: Wang, Jing, et al.
Published: (2024)
by: Wang, Jing, et al.
Published: (2024)
Equation identification for fluid flows via physics-informed neural networks
by: New, Alexander, et al.
Published: (2024)
by: New, Alexander, et al.
Published: (2024)
Learning multi-phase flow and transport in fractured porous media with auto-regressive and recurrent graph neural networks
by: Kobaisi, Mohammed Al, et al.
Published: (2025)
by: Kobaisi, Mohammed Al, et al.
Published: (2025)
DBSCAN in domains with periodic boundary conditions
by: de Wit, Xander M., et al.
Published: (2025)
by: de Wit, Xander M., et al.
Published: (2025)
Reparameterizing 4DVAR with neural fields
by: Oh, Jaemin
Published: (2025)
by: Oh, Jaemin
Published: (2025)
Nested Fourier-enhanced neural operator for efficient modeling of radiation transfer in fires
by: Jiao, Anran, et al.
Published: (2026)
by: Jiao, Anran, et al.
Published: (2026)
Physics-informed neural networks for phase-resolved data assimilation and prediction of nonlinear ocean waves
by: Ehlers, Svenja, et al.
Published: (2025)
by: Ehlers, Svenja, et al.
Published: (2025)
Prediction of flow and elastic stresses in a viscoelastic turbulent channel flow using convolutional neural networks
by: Balasubramanian, Arivazhagan G., et al.
Published: (2024)
by: Balasubramanian, Arivazhagan G., et al.
Published: (2024)
Unsupervised simulation of incompressible flows with physics- and equality- constrained artificial neural networks
by: Hu, Qifeng, et al.
Published: (2025)
by: Hu, Qifeng, et al.
Published: (2025)
Reduced-order modeling of unsteady fluid flow using neural network ensembles
by: Halder, Rakesh, et al.
Published: (2024)
by: Halder, Rakesh, et al.
Published: (2024)
Neural equilibria for long-term prediction of nonlinear conservation laws
by: Benitez, J. Antonio Lara, et al.
Published: (2025)
by: Benitez, J. Antonio Lara, et al.
Published: (2025)
Gradient-free online learning of subgrid-scale dynamics with neural emulators
by: Frezat, Hugo, et al.
Published: (2023)
by: Frezat, Hugo, et al.
Published: (2023)
Uni-Flow: a unified autoregressive-diffusion model for complex multiscale flows
by: Xue, Xiao, et al.
Published: (2026)
by: Xue, Xiao, et al.
Published: (2026)
Super-resolution of turbulent reacting flows on complex meshes using graph neural networks
by: Dash, Priyabrat, et al.
Published: (2026)
by: Dash, Priyabrat, et al.
Published: (2026)
Analysis of accuracy and efficiency of neural networks to simulate Navier-Stokes fluid flows with obstacles
by: Hespanha, Rui, et al.
Published: (2025)
by: Hespanha, Rui, et al.
Published: (2025)
Virtual domain extension for imposing boundary conditions in flow simulation using pre-trained local neural operator
by: Ye, Ximeng, et al.
Published: (2025)
by: Ye, Ximeng, et al.
Published: (2025)
A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation
by: Cao, Wenbo, et al.
Published: (2024)
by: Cao, Wenbo, et al.
Published: (2024)
A convolutional autoencoder and neural ODE framework for surrogate modeling of transient counterflow flames
by: Baykan, Mert Yakup, et al.
Published: (2026)
by: Baykan, Mert Yakup, et al.
Published: (2026)
Bridging scales in multiscale bubble growth dynamics with correlated fluctuations using neural operator learning
by: Lu, Minglei, et al.
Published: (2024)
by: Lu, Minglei, et al.
Published: (2024)
Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks
by: Ehlers, Svenja, et al.
Published: (2024)
by: Ehlers, Svenja, et al.
Published: (2024)
Reconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network
by: Mo, Yaxin, et al.
Published: (2024)
by: Mo, Yaxin, et al.
Published: (2024)
Information-theoretic machine learning for time-varying mode decomposition of separated aerodynamic flows
by: Fukami, Kai, et al.
Published: (2025)
by: Fukami, Kai, et al.
Published: (2025)
Multi-fidelity graph-based neural networks architectures to learn Navier-Stokes solutions on non-parametrized 2D domains
by: Songia, Francesco, et al.
Published: (2026)
by: Songia, Francesco, et al.
Published: (2026)
From large-eddy simulations to deep learning: A U-net model for fast urban canopy flow predictions
by: Vargiemezis, Themistoklis, et al.
Published: (2025)
by: Vargiemezis, Themistoklis, et al.
Published: (2025)
Neural ensemble Kalman filter: Data assimilation for compressible flows with shocks
by: Zhou, Xu-Hui, et al.
Published: (2026)
by: Zhou, Xu-Hui, et al.
Published: (2026)
Formulations for scalar boundedness in simulations of turbulent compressible multi-component flows using high-order finite-difference methods
by: Wang, Ye, et al.
Published: (2026)
by: Wang, Ye, et al.
Published: (2026)
Hybrid quantum physics-informed neural networks for simulating computational fluid dynamics in complex shapes
by: Sedykh, Alexandr, et al.
Published: (2023)
by: Sedykh, Alexandr, et al.
Published: (2023)
Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil
by: Sundar, Rahul, et al.
Published: (2023)
by: Sundar, Rahul, et al.
Published: (2023)
Turbulence model augmented physics informed neural networks for mean flow reconstruction
by: Patel, Yusuf, et al.
Published: (2023)
by: Patel, Yusuf, et al.
Published: (2023)
Learning of viscosity functions in rarefied gas flows with physics-informed neural networks
by: Tucny, Jean-Michel, et al.
Published: (2023)
by: Tucny, Jean-Michel, et al.
Published: (2023)
Accuracy and scalability of asynchronous compressible flow solver for transitional flows
by: Arumugam, Aswin Kumar, et al.
Published: (2025)
by: Arumugam, Aswin Kumar, et al.
Published: (2025)
A novel hybrid approach for accurate simulation of compressible multi-component flows across all-Mach number
by: Deng, Xi, et al.
Published: (2025)
by: Deng, Xi, et al.
Published: (2025)
Accelerating high order discontinuous Galerkin solvers using neural networks: 3D compressible Navier-Stokes equations
by: de Lara, Fernando Manrique, et al.
Published: (2022)
by: de Lara, Fernando Manrique, et al.
Published: (2022)
Predicting fluid-structure interaction with graph neural networks
by: Gao, Rui, et al.
Published: (2022)
by: Gao, Rui, et al.
Published: (2022)
Resolving Sharp Gradients of Unstable Singularities to Machine Precision via Neural Networks
by: Wang, Yongji, et al.
Published: (2025)
by: Wang, Yongji, et al.
Published: (2025)
An unstructured adaptive mesh refinement for steady flows based on physics-informed neural networks
by: Zhu, Yongzheng, et al.
Published: (2024)
by: Zhu, Yongzheng, et al.
Published: (2024)
Multi-fidelity physics constrained neural networks for dynamical systems
by: Zhou, Hao, et al.
Published: (2024)
by: Zhou, Hao, et al.
Published: (2024)
Similar Items
-
Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
by: Qian, Yixiao, et al.
Published: (2026) -
Physics-informed neural networks for hidden boundary detection and flow field reconstruction
by: Zhu, Yongzheng, et al.
Published: (2025) -
Efficient temporal prediction of compressible flows in irregular domains using Fourier neural operators
by: Nie, Yifan, et al.
Published: (2026) -
A Novel Paradigm in Solving Multiscale Problems
by: Wang, Jing, et al.
Published: (2024) -
Equation identification for fluid flows via physics-informed neural networks
by: New, Alexander, et al.
Published: (2024)