Saved in:
| Main Authors: | Trávníková, Veronika, Wolff, Daniel, Dirkes, Nico, Elgeti, Stefanie, von Lieres, Eric, Behr, Marek |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.04576 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quantifying data needs in surrogate modeling for flow fields in two-dimensional stirred tanks with physics-informed neural networks
by: Trávníková, Veronika, et al.
Published: (2025)
by: Trávníková, Veronika, et al.
Published: (2025)
Learnable Viscosity Modulation in Physics-Informed Neural Networks for Incompressible Flow Reconstruction
by: Xu, Ke, et al.
Published: (2026)
by: Xu, Ke, et al.
Published: (2026)
A 3D Machine Learning based Volume Of Fluid scheme without explicit interface reconstruction
by: Pintore, Moreno, et al.
Published: (2025)
by: Pintore, Moreno, et al.
Published: (2025)
Neural Networks-based Random Vortex Methods for Modelling Incompressible Flows
by: Cherepanov, Vladislav, et al.
Published: (2024)
by: Cherepanov, Vladislav, et al.
Published: (2024)
Inverting the Fundamental Diagram and Forecasting Boundary Conditions: How Machine Learning Can Improve Macroscopic Models for Traffic Flow
by: Briani, Maya, et al.
Published: (2023)
by: Briani, Maya, et al.
Published: (2023)
ARDO: A Weak Formulation Deep Neural Network Method for Elliptic and Parabolic PDEs Based on Random Differences of Test Functions
by: Cai, Wei, et al.
Published: (2025)
by: Cai, Wei, et al.
Published: (2025)
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows
by: Cao, Shuhao, et al.
Published: (2024)
by: Cao, Shuhao, et al.
Published: (2024)
Machine learning-based vorticity evolution and superresolution of homogeneous isotropic turbulence using wavelet projection
by: Asaka, Tomoki, et al.
Published: (2024)
by: Asaka, Tomoki, et al.
Published: (2024)
A Hybrid CNN-Cheby-KAN Framework for Efficient Prediction of Two-Dimensional Airfoil Pressure Distribution
by: Chen, Yaohong, et al.
Published: (2025)
by: Chen, Yaohong, et al.
Published: (2025)
Learning Flame Evolution Operator under Hybrid Darrieus Landau and Diffusive Thermal Instability
by: Yu, Rixin, et al.
Published: (2024)
by: Yu, Rixin, et al.
Published: (2024)
Physics-Informed Neural Networks: Bridging the Divide Between Conservative and Non-Conservative Equations
by: Neelan, Arun Govind, et al.
Published: (2025)
by: Neelan, Arun Govind, et al.
Published: (2025)
All Equalities Are Equal, but Some Are More Equal Than Others: The Effect of Implementation Aliasing on the Numerical Solution to Conservation Equations
by: Trojak, Will, et al.
Published: (2019)
by: Trojak, Will, et al.
Published: (2019)
Autoregressive prediction of 2D MHD dynamics inferred from deep learning modeling
by: Kivarkis, David, et al.
Published: (2026)
by: Kivarkis, David, et al.
Published: (2026)
WAKESET: A Large-Scale, High-Reynolds Number Flow Dataset for Machine Learning of Turbulent Wake Dynamics
by: Cooper-Baldock, Zachary, et al.
Published: (2026)
by: Cooper-Baldock, Zachary, et al.
Published: (2026)
Global well-posedness of strong solutions to a bulk-surface Navier-Stokes-Cahn-Hilliard model with non-degenerate mobilities in two dimensions
by: Stange, Jonas
Published: (2025)
by: Stange, Jonas
Published: (2025)
Scientific machine learning for closure models in multiscale problems: a review
by: Sanderse, Benjamin, et al.
Published: (2024)
by: Sanderse, Benjamin, et al.
Published: (2024)
Quantum Lattice Boltzmann with Denoising Collision Operators
by: Duong, Trong, et al.
Published: (2026)
by: Duong, Trong, et al.
Published: (2026)
Temporal Lifting as Latent-Space Regularization for Continuous-Time Flow Models in AI Systems
by: Camlin, Jeffrey
Published: (2025)
by: Camlin, Jeffrey
Published: (2025)
Deep Micro Solvers for Rough-Wall Stokes Flow in a Heterogeneous Multiscale Method
by: Ström, Emanuel, et al.
Published: (2025)
by: Ström, Emanuel, et al.
Published: (2025)
A thermodynamically consistent model for bulk-surface viscous fluid mixtures: Model derivation and mathematical analysis
by: Knopf, Patrik, et al.
Published: (2025)
by: Knopf, Patrik, et al.
Published: (2025)
On the Stokes system in cylindrical domains
by: Rencławowicz, Joanna, et al.
Published: (2021)
by: Rencławowicz, Joanna, et al.
Published: (2021)
A robust and stable hybrid neural network/finite element method for 2D flows that generalizes to different geometries
by: Jendersie, Robert, et al.
Published: (2026)
by: Jendersie, Robert, et al.
Published: (2026)
Differentiable DG with Neural Operator Source Term Correction
by: Kang, Shinhoo, et al.
Published: (2023)
by: Kang, Shinhoo, et al.
Published: (2023)
A Flow-rate-conserving CNN-based Domain Decomposition Method for Blood Flow Simulations
by: Klaes, Simon, et al.
Published: (2025)
by: Klaes, Simon, et al.
Published: (2025)
Homogenization of the Navier-Stokes equations in perforated domains in the inviscid limit
by: Höfer, Richard M.
Published: (2022)
by: Höfer, Richard M.
Published: (2022)
On Topology of Three-dimensional Continua with Singular Points
by: Liang, Hao, et al.
Published: (2025)
by: Liang, Hao, et al.
Published: (2025)
DrivAer Transformer: A high-precision and fast prediction method for vehicle aerodynamic drag coefficient based on the DrivAerNet++ dataset
by: He, Jiaqi, et al.
Published: (2025)
by: He, Jiaqi, et al.
Published: (2025)
A Parameter-Driven Physics-Informed Neural Network Framework for Solving Two-Parameter Singular Perturbation Problems Involving Boundary Layers
by: Boro, Pradanya, et al.
Published: (2025)
by: Boro, Pradanya, et al.
Published: (2025)
Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2024)
Embedding Graphs of Simple Treewidth into Sparse Products
by: Hendrey, Kevin, et al.
Published: (2025)
by: Hendrey, Kevin, et al.
Published: (2025)
Driving Viscous Hydrodynamics in Bulk Electron Flow in Graphene Using Micromagnets
by: Engdahl, Jack N., et al.
Published: (2023)
by: Engdahl, Jack N., et al.
Published: (2023)
Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models
by: Liu, Qiang, et al.
Published: (2023)
by: Liu, Qiang, et al.
Published: (2023)
Beyond the Kolmogorov Barrier: A Learnable Weighted Hybrid Autoencoder for Model Order Reduction
by: Somasekharan, Nithin, et al.
Published: (2024)
by: Somasekharan, Nithin, et al.
Published: (2024)
From molecular model to tensor model of nematic liquid crystals through entropy decomposition
by: Shi, Baoming, et al.
Published: (2026)
by: Shi, Baoming, et al.
Published: (2026)
Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media
by: Fernández-Godino, M. Giselle, et al.
Published: (2025)
by: Fernández-Godino, M. Giselle, et al.
Published: (2025)
Flow reversal of the Stokes system with localized boundary data in the half space
by: Chang, Tongkeun, et al.
Published: (2026)
by: Chang, Tongkeun, et al.
Published: (2026)
HARPPP: Autonomous Geometric Design Optimisation of Stirred Tank Reactor Impellers and Baffles
by: Nicusan, A. Leonard, et al.
Published: (2025)
by: Nicusan, A. Leonard, et al.
Published: (2025)
A numerical study of the run-up and the force exerted on a vertical wall by a solitary wave propagating over two tandem trenches and impinging on the wall
by: Athanassoulis, Gerassimos A., et al.
Published: (2019)
by: Athanassoulis, Gerassimos A., et al.
Published: (2019)
Teaching and Learning under Deductive Errors
by: Telle, Jan Arne, et al.
Published: (2026)
by: Telle, Jan Arne, et al.
Published: (2026)
Net-Zero: A Comparative Study on Neural Network Design for Climate-Economic PDEs Under Uncertainty
by: Rodriguez-Pardo, Carlos, et al.
Published: (2025)
by: Rodriguez-Pardo, Carlos, et al.
Published: (2025)
Similar Items
-
Quantifying data needs in surrogate modeling for flow fields in two-dimensional stirred tanks with physics-informed neural networks
by: Trávníková, Veronika, et al.
Published: (2025) -
Learnable Viscosity Modulation in Physics-Informed Neural Networks for Incompressible Flow Reconstruction
by: Xu, Ke, et al.
Published: (2026) -
A 3D Machine Learning based Volume Of Fluid scheme without explicit interface reconstruction
by: Pintore, Moreno, et al.
Published: (2025) -
Neural Networks-based Random Vortex Methods for Modelling Incompressible Flows
by: Cherepanov, Vladislav, et al.
Published: (2024) -
Inverting the Fundamental Diagram and Forecasting Boundary Conditions: How Machine Learning Can Improve Macroscopic Models for Traffic Flow
by: Briani, Maya, et al.
Published: (2023)