Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
Fuente:
arXiv
Saved in:
| Main Authors: | Toshev, Artur P., Erbesdobler, Jonas A., Adams, Nikolaus A., Brandstetter, Johannes |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework
by: Toshev, Artur P., et al.
Published: (2024)
by: Toshev, Artur P., et al.
Published: (2024)
Towards Multi-Fidelity Scaling Laws of Neural Surrogates in CFD
by: Setinek, Paul, et al.
Published: (2025)
by: Setinek, Paul, et al.
Published: (2025)
LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics
by: Xiao, Qisong, et al.
Published: (2026)
by: Xiao, Qisong, et al.
Published: (2026)
Fluid Intelligence: A Forward Look on AI Foundation Models in Computational Fluid Dynamics
by: Ashton, Neil, et al.
Published: (2025)
by: Ashton, Neil, et al.
Published: (2025)
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
by: Ma, Qilong, et al.
Published: (2024)
by: Ma, Qilong, et al.
Published: (2024)
Impact of Loss Weight and Model Complexity on Physics-Informed Neural Networks for Computational Fluid Dynamics
by: Chou, Yi En, et al.
Published: (2025)
by: Chou, Yi En, et al.
Published: (2025)
Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
by: Alkin, Benedikt, et al.
Published: (2024)
by: Alkin, Benedikt, et al.
Published: (2024)
A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulations
by: Gao, Rui, et al.
Published: (2022)
by: Gao, Rui, et al.
Published: (2022)
JAX-Fluids 2.0: Towards HPC for Differentiable CFD of Compressible Two-phase Flows
by: Bezgin, Deniz A., et al.
Published: (2024)
by: Bezgin, Deniz A., et al.
Published: (2024)
Neural Kinematic Bases for Fluids
by: Liu, Yibo, et al.
Published: (2025)
by: Liu, Yibo, et al.
Published: (2025)
Hybrid Neural-MPM for Interactive Fluid Simulations in Real-Time
by: Xu, Jingxuan, et al.
Published: (2025)
by: Xu, Jingxuan, et al.
Published: (2025)
OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics
by: Zhang, Rui, et al.
Published: (2025)
by: Zhang, Rui, et al.
Published: (2025)
Towards high-order consistency and convergence of conservative SPH approximations
by: Zhang, Bo, et al.
Published: (2024)
by: Zhang, Bo, et al.
Published: (2024)
The compressible Neural Particle Method for Simulating Compressible Viscous Fluid Flows
by: Shibukawa, Masato, et al.
Published: (2025)
by: Shibukawa, Masato, et al.
Published: (2025)
An ALE-Consistent Graph Neural Operator-Transformer Framework for Fluid-Structure Interaction
by: Zhao, Shihang, et al.
Published: (2026)
by: Zhao, Shihang, et al.
Published: (2026)
HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
by: Lagemann, Christian, et al.
Published: (2025)
by: Lagemann, Christian, et al.
Published: (2025)
DSO: Dual-Scale Neural Operators for Stable Long-term Fluid Dynamics Forecasting
by: Dong, Huanshuo, et al.
Published: (2026)
by: Dong, Huanshuo, et al.
Published: (2026)
Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
by: de Aguiar, Diego A., et al.
Published: (2024)
by: de Aguiar, Diego A., et al.
Published: (2024)
DiffFluid: Plain Diffusion Models are Effective Predictors of Flow Dynamics
by: Luo, Dongyu, et al.
Published: (2024)
by: Luo, Dongyu, et al.
Published: (2024)
Multi-scale Dynamic Wake Modeling and Prediction of Floating Offshore Wind Turbines via Physics-Informed Neural Networks and Fourier Neural Operators
by: Dong, Guodan, et al.
Published: (2026)
by: Dong, Guodan, et al.
Published: (2026)
Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction
by: Schwarz, Henning, et al.
Published: (2026)
by: Schwarz, Henning, et al.
Published: (2026)
Inpainting Computational Fluid Dynamics with Deep Learning
by: Shu, Dule, et al.
Published: (2024)
by: Shu, Dule, et al.
Published: (2024)
HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics
by: Ashton, Neil, et al.
Published: (2026)
by: Ashton, Neil, et al.
Published: (2026)
PAINT: Parallel-in-time Neural Twins for Dynamical System Reconstruction
by: Radler, Andreas, et al.
Published: (2025)
by: Radler, Andreas, et al.
Published: (2025)
Neural Physics: Using AI Libraries to Develop Physics-Based Solvers for Incompressible Computational Fluid Dynamics
by: Chen, Boyang, et al.
Published: (2024)
by: Chen, Boyang, et al.
Published: (2024)
Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
by: Grozavescu, Rares, et al.
Published: (2026)
by: Grozavescu, Rares, et al.
Published: (2026)
MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
by: Yang, Tianyue, et al.
Published: (2026)
by: Yang, Tianyue, et al.
Published: (2026)
Transported Memory Networks accelerating Computational Fluid Dynamics
by: Schulz, Matthias, et al.
Published: (2025)
by: Schulz, Matthias, et al.
Published: (2025)
Model-Agnostic AI Framework with Explicit Time Integration for Long-Term Fluid Dynamics Prediction
by: Yang, Sunwoong, et al.
Published: (2024)
by: Yang, Sunwoong, et al.
Published: (2024)
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)
by: Kurz, Marius, et al.
Published: (2025)
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling
by: Oommen, Vivek, et al.
Published: (2024)
by: Oommen, Vivek, et al.
Published: (2024)
Combining Machine Learning with Computational Fluid Dynamics using OpenFOAM and SmartSim
by: Maric, Tomislav, et al.
Published: (2024)
by: Maric, Tomislav, et al.
Published: (2024)
Mean flow data assimilation using physics-constrained Graph Neural Networks
by: Quattromini, M., et al.
Published: (2024)
by: Quattromini, M., et al.
Published: (2024)
FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)
by: Raut, Riddhiman, et al.
Published: (2025)
Differentiable Autoencoding Neural Operator for Interpretable and Integrable Latent Space Modeling
by: Viknesh, Siva, et al.
Published: (2025)
by: Viknesh, Siva, et al.
Published: (2025)
Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies
by: Kumar, Prashant, et al.
Published: (2026)
by: Kumar, Prashant, et al.
Published: (2026)
Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network
by: Xu, Weiming, et al.
Published: (2023)
by: Xu, Weiming, et al.
Published: (2023)
Addressing A Posteriori Performance Degradation in Neural Network Subgrid Stress Models
by: Wu, Andy, et al.
Published: (2025)
by: Wu, Andy, et al.
Published: (2025)
Hybrid Fourier Neural Operator-Lattice Boltzmann Method
by: Junk, Alexandra, et al.
Published: (2026)
by: Junk, Alexandra, et al.
Published: (2026)
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)
Similar Items
-
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework
by: Toshev, Artur P., et al.
Published: (2024) -
Towards Multi-Fidelity Scaling Laws of Neural Surrogates in CFD
by: Setinek, Paul, et al.
Published: (2025) -
LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics
by: Xiao, Qisong, et al.
Published: (2026) -
Fluid Intelligence: A Forward Look on AI Foundation Models in Computational Fluid Dynamics
by: Ashton, Neil, et al.
Published: (2025) -
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
by: Ma, Qilong, et al.
Published: (2024)