Deep Neural Networks with 3D Point Clouds for Empirical Friction Measurements in Hydrodynamic Flood Models
Fuente:
arXiv
Saved in:
| Main Authors: | Haces-Garcia, Francisco, Kotzamanis, Vasileios, Glennie, Craig, Rifai, Hanadi |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive Sampling for Hydrodynamic Stability
by: Singh, Anshima, et al.
Published: (2025)
by: Singh, Anshima, et al.
Published: (2025)
Lagrangian Ellipsoid Diagnostics for Stochastic Hydrodynamics: Source--Sink Modeling of Deforming Particle Clouds
by: Chertkov, Michael
Published: (2026)
by: Chertkov, Michael
Published: (2026)
Hydrodynamic Origin of Friction Between Suspended Rough Particles
by: Minten, Jake, et al.
Published: (2025)
by: Minten, Jake, et al.
Published: (2025)
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)
by: Kurz, Marius, et al.
Published: (2025)
Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
by: Kim, Hojin, et al.
Published: (2025)
by: Kim, Hojin, 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)
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework
by: Toshev, Artur P., et al.
Published: (2024)
by: Toshev, Artur P., et al.
Published: (2024)
Modeling Multivariable High-resolution 3D Urban Microclimate Using Localized Fourier Neural Operator
by: Qin, Shaoxiang, et al.
Published: (2024)
by: Qin, Shaoxiang, 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)
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)
Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
by: Rozet, François, et al.
Published: (2025)
by: Rozet, François, et al.
Published: (2025)
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)
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)
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)
BLISSNet: Deep Operator Learning for Fast and Accurate Flow Reconstruction from Sparse Sensor Measurements
by: Veremchuk, Maksym, et al.
Published: (2026)
by: Veremchuk, Maksym, et al.
Published: (2026)
Deep Operator Learning for High-Fidelity Fluid Flow Field Reconstruction from Sparse Sensor Measurements
by: Dang, Hiep Vo, et al.
Published: (2024)
by: Dang, Hiep Vo, et al.
Published: (2024)
FLRNet: A Deep Learning Method for Regressive Reconstruction of Flow Field From Limited Sensor Measurements
by: Nguyen, Phong C. H., et al.
Published: (2024)
by: Nguyen, Phong C. H., et al.
Published: (2024)
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)
Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries
by: Kashefi, Ali, et al.
Published: (2025)
by: Kashefi, Ali, et al.
Published: (2025)
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)
Reduced-Order Hydrodynamic Modelling of a Sphere Near a Wall Using Sparse Regression and Neural Operators
by: Hoffman, Zev, et al.
Published: (2025)
by: Hoffman, Zev, 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)
Surrogate Modeling of 3D Rayleigh-Benard Convection with Equivariant Autoencoders
by: Fromme, Fynn, et al.
Published: (2025)
by: Fromme, Fynn, et al.
Published: (2025)
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
by: Lienen, Marten, et al.
Published: (2023)
by: Lienen, Marten, et al.
Published: (2023)
TripNet: Learning Large-scale High-fidelity 3D Car Aerodynamics with Triplane Networks
by: Chen, Qian, et al.
Published: (2025)
by: Chen, Qian, et al.
Published: (2025)
Fusion-DeepONet: A Data-Efficient Neural Operator for Geometry-Dependent Hypersonic and Supersonic Flows
by: Peyvan, Ahmad, et al.
Published: (2025)
by: Peyvan, Ahmad, et al.
Published: (2025)
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)
Mean flow data assimilation using physics-constrained Graph Neural Networks
by: Quattromini, M., et al.
Published: (2024)
by: Quattromini, M., et al.
Published: (2024)
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)
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)
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)
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)
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)
Real-scale Smoothed Particle Hydrodynamics Tsunami Runup Modelling, with application to 3-D tsunami urban flows in Cilacap, South Java, Indonesia
by: Dignan, Jack, et al.
Published: (2025)
by: Dignan, Jack, et al.
Published: (2025)
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)
Solving Euler equations with Multiple Discontinuities via Separation-Transfer Physics-Informed Neural Networks
by: Wang, Chuanxing, et al.
Published: (2025)
by: Wang, Chuanxing, et al.
Published: (2025)
Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network
by: Gu, Yuxuan, et al.
Published: (2024)
by: Gu, Yuxuan, et al.
Published: (2024)
Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments
by: Shende, Takshak, et al.
Published: (2026)
by: Shende, Takshak, et al.
Published: (2026)
Similar Items
-
Adaptive Sampling for Hydrodynamic Stability
by: Singh, Anshima, et al.
Published: (2025) -
Lagrangian Ellipsoid Diagnostics for Stochastic Hydrodynamics: Source--Sink Modeling of Deforming Particle Clouds
by: Chertkov, Michael
Published: (2026) -
Hydrodynamic Origin of Friction Between Suspended Rough Particles
by: Minten, Jake, et al.
Published: (2025) -
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025) -
Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
by: Kim, Hojin, et al.
Published: (2025)