Saved in:
| Main Authors: | de Aguiar, Diego A., França, Hugo L., Oishi, Cassio M. |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.16144 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
by: Diego A. de Aguiar, et al.
Published: (2025)
by: Diego A. de Aguiar, et al.
Published: (2025)
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)
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)
Multi-resolution Physics-Aware Recurrent Convolutional Neural Network for Complex Flows
by: Cheng, Xinlun, et al.
Published: (2025)
by: Cheng, Xinlun, et al.
Published: (2025)
Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
by: Toshev, Artur P., et al.
Published: (2024)
by: Toshev, Artur P., et al.
Published: (2024)
Knowledge-Based Convolutional Neural Network for the Simulation and Prediction of Two-Phase Darcy Flows
by: Elabid, Zakaria, et al.
Published: (2024)
by: Elabid, Zakaria, 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)
Data-driven Learning of Probabilistic Model of Binary Droplet Collision for Spray Simulation
by: Xu, Weiming, et al.
Published: (2026)
by: Xu, Weiming, et al.
Published: (2026)
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)
Odd Droplets: Fluids with Odd Viscosity and Highly Deformable Interfaces
by: França, Hugo, et al.
Published: (2025)
by: França, Hugo, et al.
Published: (2025)
Physics-Informed Neural Network Approaches for Sparse Data Flow Reconstruction of Unsteady Flow Around Complex Geometries
by: Malineni, Vamsi Sai Krishna, et al.
Published: (2025)
by: Malineni, Vamsi Sai Krishna, et al.
Published: (2025)
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)
Predicting Flow Dynamics using Diffusion Models
by: Gachnang, Yannick, et al.
Published: (2025)
by: Gachnang, Yannick, et al.
Published: (2025)
A Kernel-based Resource-efficient Neural Surrogate for Multi-fidelity Prediction of Aerodynamic Field
by: Sarker, Apurba, et al.
Published: (2025)
by: Sarker, Apurba, et al.
Published: (2025)
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)
MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
by: Yang, Tianyue, et al.
Published: (2026)
by: Yang, Tianyue, et al.
Published: (2026)
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)
by: Kurz, Marius, 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)
Machine Learning in Viscoelastic Fluids via Energy-Based Kernel Embedding
by: Otto, Samuel E., et al.
Published: (2024)
by: Otto, Samuel E., et al.
Published: (2024)
Hard Constraint Projection in a Physics Informed Neural Network
by: Horne, Miranda J. S., et al.
Published: (2026)
by: Horne, Miranda J. S., et al.
Published: (2026)
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
by: Ma, Qilong, et al.
Published: (2024)
by: Ma, Qilong, et al.
Published: (2024)
A Mesh-Adaptive Hypergraph Neural Network for Unsteady Flow Around Oscillating and Rotating Structures
by: Gao, Rui, et al.
Published: (2025)
by: Gao, Rui, et al.
Published: (2025)
Transported Memory Networks accelerating Computational Fluid Dynamics
by: Schulz, Matthias, et al.
Published: (2025)
by: Schulz, Matthias, et al.
Published: (2025)
FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)
by: Raut, Riddhiman, et al.
Published: (2025)
MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
by: Garnier, Paul, et al.
Published: (2025)
by: Garnier, Paul, et al.
Published: (2025)
Periodicity-Enforced Neural Network for Designing Deterministic Lateral Displacement Devices
by: Lee, Andrew, et al.
Published: (2025)
by: Lee, Andrew, et al.
Published: (2025)
Quantifying Out-of-Training Uncertainty of Neural-Network based Turbulence Closures
by: Grogan, Cody, et al.
Published: (2025)
by: Grogan, Cody, et al.
Published: (2025)
Geometry Matters: Benchmarking Scientific ML Approaches for Flow Prediction around Complex Geometries
by: Rabeh, Ali, et al.
Published: (2024)
by: Rabeh, Ali, et al.
Published: (2024)
Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study
by: Abbasi, Jassem, et al.
Published: (2025)
by: Abbasi, Jassem, et al.
Published: (2025)
FMEnets: Flow, Material, and Energy networks for non-ideal plug flow reactor design
by: Wu, Chenxi, et al.
Published: (2025)
by: Wu, Chenxi, 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)
Droplet Deformation and Emulsion Rheology in Two-Dimensional Odd Stokes Flow
by: Appleford, Thomas, et al.
Published: (2026)
by: Appleford, Thomas, et al.
Published: (2026)
Can physical information aid the generalization ability of Neural Networks for hydraulic modeling?
by: Guglielmo, Gianmarco, et al.
Published: (2024)
by: Guglielmo, Gianmarco, et al.
Published: (2024)
Invariant Control Strategies for Active Flow Control using Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)
by: Kurz, Marius, et al.
Published: (2025)
From Models To Experiments: Shallow Recurrent Decoder Networks on the DYNASTY Experimental Facility
by: Riva, Stefano, et al.
Published: (2025)
by: Riva, Stefano, et al.
Published: (2025)
Predicting Time-Dependent Flow Over Complex Geometries Using Operator Networks
by: Rabeh, Ali, et al.
Published: (2025)
by: Rabeh, Ali, et al.
Published: (2025)
Inverse Design of Optimal Stern Shape with Convolutional Neural Network-based Pressure Distribution
by: Oh, Sang-jin, et al.
Published: (2025)
by: Oh, Sang-jin, et al.
Published: (2025)
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction
by: Cao, Yadi, et al.
Published: (2024)
by: Cao, Yadi, et al.
Published: (2024)
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)
Similar Items
-
Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
by: Diego A. de Aguiar, et al.
Published: (2025) -
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) -
Conditional Neural Field based Reduced Order Model for Dynamic Ditching Load Prediction
by: Schwarz, Henning, et al.
Published: (2026) -
A Finite Element-Inspired Hypergraph Neural Network: Application to Fluid Dynamics Simulations
by: Gao, Rui, et al.
Published: (2022) -
Multi-resolution Physics-Aware Recurrent Convolutional Neural Network for Complex Flows
by: Cheng, Xinlun, et al.
Published: (2025)