Cross-Field Interface-Aware Neural Operators for Multiphase Flow Simulation
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Zhenzhong, Zhang, Xin, Liao, Jun, Jiang, Min |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Physics-Informed Neural Networks for Enhanced Interface Preservation in Lattice Boltzmann Multiphase Simulations
by: Li, Yue, et al.
Published: (2025)
by: Li, Yue, et al.
Published: (2025)
Spatially-Aware Diffusion Models with Cross-Attention for Global Field Reconstruction with Sparse Observations
by: Zhuang, Yilin, et al.
Published: (2024)
by: Zhuang, Yilin, et al.
Published: (2024)
Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows
by: Yan, Mengtao, et al.
Published: (2025)
by: Yan, Mengtao, 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)
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)
LatentFlow: Cross-Frequency Experimental Flow Reconstruction from Sparse Pressure via Latent Mapping
by: Liu, Junle, et al.
Published: (2025)
by: Liu, Junle, 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)
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)
Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction
by: Oommen, Vivek, et al.
Published: (2025)
by: Oommen, Vivek, et al.
Published: (2025)
Solving the Discretised Multiphase Flow Equations with Interface Capturing on Structured Grids Using Machine Learning Libraries
by: Chen, Boyang, et al.
Published: (2024)
by: Chen, Boyang, et al.
Published: (2024)
Project and Generate: Divergence-Free Neural Operators for Incompressible Flows
by: Li, Xigui, et al.
Published: (2026)
by: Li, Xigui, et al.
Published: (2026)
Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance
by: Wu, Hao, et al.
Published: (2024)
by: Wu, Hao, et al.
Published: (2024)
OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows
by: Hickling, Tom, et al.
Published: (2025)
by: Hickling, Tom, et al.
Published: (2025)
Learning Pore-scale Multiphase Flow from 4D Velocimetry
by: Wang, Chunyang, et al.
Published: (2026)
by: Wang, Chunyang, et al.
Published: (2026)
Simulating Three-dimensional Turbulence with Physics-informed Neural Networks
by: Wang, Sifan, et al.
Published: (2025)
by: Wang, Sifan, et al.
Published: (2025)
Flow reconstruction in time-varying geometries using graph neural networks
by: Danciu, Bogdan A., et al.
Published: (2024)
by: Danciu, Bogdan A., et al.
Published: (2024)
Enhancing Graph U-Nets for Mesh-Agnostic Spatio-Temporal Flow Prediction
by: Yang, Sunwoong, et al.
Published: (2024)
by: Yang, Sunwoong, et al.
Published: (2024)
Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence
by: Mukhopadhyay, Payel, et al.
Published: (2026)
by: Mukhopadhyay, Payel, et al.
Published: (2026)
FluidFlow: a flow-matching generative model for fluid dynamics surrogates on unstructured meshes
by: Ramos, David, et al.
Published: (2026)
by: Ramos, David, et al.
Published: (2026)
A Multi-fidelity Double-Delta Wing Dataset and Empirical Scaling Laws for GNN-based Aerodynamic Field Surrogate
by: Shen, Yiren, et al.
Published: (2025)
by: Shen, Yiren, et al.
Published: (2025)
Physics-informed Neural-operator Predictive Control for Drag Reduction in Turbulent Flows
by: Zhao, Zelin, et al.
Published: (2025)
by: Zhao, Zelin, 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)
Multiscale Graph Neural Network for Turbulent Flow-Thermal Prediction Around a Complex-Shaped Pin-Fin
by: Raut, Riddhiman, et al.
Published: (2025)
by: Raut, Riddhiman, et al.
Published: (2025)
Finite-difference-informed graph network for solving steady-state incompressible flows on block-structured grids
by: Zou, Yiye, et al.
Published: (2024)
by: Zou, Yiye, et al.
Published: (2024)
Turb-L1: Achieving Long-term Turbulence Tracing By Tackling Spectral Bias
by: Wu, Hao, et al.
Published: (2025)
by: Wu, Hao, et al.
Published: (2025)
MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
by: Yang, Tianyue, et al.
Published: (2026)
by: Yang, Tianyue, et al.
Published: (2026)
Neural Operator-Based Proxy for Reservoir Simulations Considering Varying Well Settings, Locations, and Permeability Fields
by: Badawi, Daniel, et al.
Published: (2024)
by: Badawi, Daniel, et al.
Published: (2024)
HydroGym: A Reinforcement Learning Platform for Fluid Dynamics
by: Lagemann, Christian, et al.
Published: (2025)
by: Lagemann, Christian, et al.
Published: (2025)
Deep Reinforcement Learning in Action: Real-Time Control of Vortex-Induced Vibrations
by: Sababha, Hussam, et al.
Published: (2025)
by: Sababha, Hussam, et al.
Published: (2025)
Shape Invariant 3D-Variational Autoencoder: Super Resolution in Turbulence flow
by: Maurya, Anuraj
Published: (2025)
by: Maurya, Anuraj
Published: (2025)
An Empirical Wall-Pressure Spectrum Model for Aeroacoustic Predictions Based on Symbolic Regression
by: Bolívar, Laura Botero, et al.
Published: (2025)
by: Bolívar, Laura Botero, et al.
Published: (2025)
Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction
by: Tonti, Federica, et al.
Published: (2026)
by: Tonti, Federica, et al.
Published: (2026)
PointSAGE: Mesh-independent superresolution approach to fluid flow predictions
by: Sarkar, Rajat, et al.
Published: (2024)
by: Sarkar, Rajat, et al.
Published: (2024)
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
by: Xu, Qingsong, et al.
Published: (2023)
by: Xu, Qingsong, et al.
Published: (2023)
Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach
by: Pinheiro, Nathalie C., et al.
Published: (2026)
by: Pinheiro, Nathalie C., et al.
Published: (2026)
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)
Uncertainty-Aware Flow Field Reconstruction Using SVGP Kolmogorov-Arnold Networks
by: Ju, Y. Sungtaek
Published: (2025)
by: Ju, Y. Sungtaek
Published: (2025)
Shock-Aware Physics-Guided Fusion-DeepONet Operator for Rarefied Micro-Nozzle Flows
by: Roohi, Ehsan, et al.
Published: (2025)
by: Roohi, Ehsan, et al.
Published: (2025)
Predicting The Evolution of Interfaces with Fourier Neural Operators
by: Guida, Paolo, et al.
Published: (2025)
by: Guida, Paolo, et al.
Published: (2025)
PINNfluence: Influence Functions for Physics-Informed Neural Networks
by: Naujoks, Jonas R., et al.
Published: (2024)
by: Naujoks, Jonas R., et al.
Published: (2024)
Similar Items
-
Physics-Informed Neural Networks for Enhanced Interface Preservation in Lattice Boltzmann Multiphase Simulations
by: Li, Yue, et al.
Published: (2025) -
Spatially-Aware Diffusion Models with Cross-Attention for Global Field Reconstruction with Sparse Observations
by: Zhuang, Yilin, et al.
Published: (2024) -
Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows
by: Yan, Mengtao, et al.
Published: (2025) -
DSO: Dual-Scale Neural Operators for Stable Long-term Fluid Dynamics Forecasting
by: Dong, Huanshuo, et al.
Published: (2026) -
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling
by: Oommen, Vivek, et al.
Published: (2024)