Copertina

Convolutional autoencoders for the reconstruction of three-dimensional interfacial multiphase flows

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cutforth, Murray, Mirjalili, Shahab
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computational Engineering, Finance, and Science Machine Learning Fluid Dynamics
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Physically Interpretable Representation and Controlled Generation for Turbulence Data
di: Fan, Tiffany, et al.
Pubblicazione: (2025)

Model-based deep reinforcement learning for accelerated learning from flow simulations
di: Weiner, Andre, et al.
Pubblicazione: (2024)

FluidFormer: Transformer with Continuous Convolution for Particle-based Fluid Simulation
di: Wang, Nianyi, et al.
Pubblicazione: (2025)

Learning Fluid-Structure Interaction with Physics-Informed Machine Learning and Immersed Boundary Methods
di: Farea, Afrah, et al.
Pubblicazione: (2025)

A Residual Guided strategy with Generative Adversarial Networks in training Physics-Informed Transformer Networks
di: Zhang, Ziyang, et al.
Pubblicazione: (2025)

Scientific Machine Learning of Flow Resistance Using Universal Shallow Water Equations with Differentiable Programming
di: Liu, Xiaofeng, et al.
Pubblicazione: (2025)

Generalization of Urban Wind Environment Using Fourier Neural Operator Across Different Wind Directions and Cities
di: Chen, Cheng, et al.
Pubblicazione: (2025)

Multi-level datasets training method in Physics-Informed Neural Networks
di: Tsai, Yao-Hsuan, et al.
Pubblicazione: (2025)

JAX-Fluids 2.0: Towards HPC for Differentiable CFD of Compressible Two-phase Flows
di: Bezgin, Deniz A., et al.
Pubblicazione: (2024)

Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective
di: Yang, Sunwoong, et al.
Pubblicazione: (2024)

C(NN)FD -- a deep learning framework for turbomachinery CFD analysis
di: Bruni, Giuseppe, et al.
Pubblicazione: (2023)

AhmedML: High-Fidelity Computational Fluid Dynamics Dataset for Incompressible, Low-Speed Bluff Body Aerodynamics
di: Ashton, Neil, et al.
Pubblicazione: (2024)

Deep learning modelling of manufacturing and build variations on multi-stage axial compressors aerodynamics
di: Bruni, Giuseppe, et al.
Pubblicazione: (2023)

DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics
di: Ashton, Neil, et al.
Pubblicazione: (2024)

A TVD neural network closure and application to turbulent combustion
di: Suh, Seung Won, et al.
Pubblicazione: (2024)

DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction
di: Elrefaie, Mohamed, et al.
Pubblicazione: (2024)

NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design
di: Yagoubi, Mouadh, et al.
Pubblicazione: (2024)

A MgNO Method for Multiphase Flow in Porous Media
di: Liu, Xinliang, et al.
Pubblicazione: (2024)

WindsorML: High-Fidelity Computational Fluid Dynamics Dataset For Automotive Aerodynamics
di: Ashton, Neil, et al.
Pubblicazione: (2024)

Investigate the efficiency of incompressible flow simulations on CPUs and GPUs with BSAMR
di: Liu, Dewen, et al.
Pubblicazione: (2024)

Deep learning-based predictive modelling of transonic flow over an aerofoil
di: Chen, Li-Wei, et al.
Pubblicazione: (2024)

Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
di: Barwey, Shivam, et al.
Pubblicazione: (2024)

Prediction of Steady-State Flow through Porous Media Using Machine Learning Models
di: Wang, Jinhong, et al.
Pubblicazione: (2026)

A weakly compressible SPH method for RANS simulation of wall-bounded turbulent flows
di: Wang, Feng, et al.
Pubblicazione: (2025)

Hydrodynamics of bubble flow through a porous medium with applications to packed bed reactors
di: Nagrani, Pranay P., et al.
Pubblicazione: (2023)

Density-based topology optimization for turbulent fluid flow using the standard k-epsilon RANS model with wall-functions imposed through an implicit wall penalty formulation
di: Bayat, Amirhossein, et al.
Pubblicazione: (2026)

An Interpretable Data-Driven Model of the Flight Dynamics of Hawks
di: France, Lydia, et al.
Pubblicazione: (2026)

Aero-Nef: Neural Fields for Rapid Aircraft Aerodynamics Simulations
di: Catalani, Giovanni, et al.
Pubblicazione: (2024)

DrivAerNet++: A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
di: Elrefaie, Mohamed, et al.
Pubblicazione: (2024)

Synthetic Lagrangian Turbulence by Generative Diffusion Models
di: Li, Tianyi, et al.
Pubblicazione: (2023)

STONet: A neural operator for modeling solute transport in micro-cracked reservoirs
di: Haghighat, Ehsan, et al.
Pubblicazione: (2024)

Development of a Cost-Effective Simulation Tool for Loss of Flow Accident Transients in High-Temperature Gas-cooled Reactors
di: Liu, Bo, et al.
Pubblicazione: (2025)

Multi-scale topology optimization of porous heat sinks with voided lattice structure using a two-layer Darcy-Forchheimer model
di: Saito, Tatsuki, et al.
Pubblicazione: (2025)

Physics-Informed Machine Learning Approach in Augmenting RANS Models Using DNS Data and DeepInsight Method on FDA Nozzle
di: Geshani, Hossein, et al.
Pubblicazione: (2025)

A fluid--peridynamic structure model of deformation and damage of microchannels
di: Wang, Ziyu, et al.
Pubblicazione: (2025)

Accelerated Computational Fluid Dynamics Simulations of Microfluidic Devices by Exploiting Higher Levels of Abstraction
di: Takken, Michel, et al.
Pubblicazione: (2023)

Topological Separation of Vortices
di: Zafar, Adeel, et al.
Pubblicazione: (2024)

Data repairing and resolution enhancement using data-driven modal decomposition and deep learning
di: Hetherington, A., et al.
Pubblicazione: (2024)

Bayesian Model Selection for Complex Flows of Yield Stress Fluids
di: Rinkens, Aricia, et al.
Pubblicazione: (2026)

On the use of high order central difference schemes for differential equation based wall distance computations
di: Kakumani, Hemanth Chandra Vamsi, et al.
Pubblicazione: (2021)