Cover Image

Data-driven Learning of Probabilistic Model of Binary Droplet Collision for Spray Simulation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Weiming, Yang, Tao, Zhang, Peng
Format:	Preprint
Published:	2026
Subjects:	Fluid Dynamics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network
by: Xu, Weiming, et al.
Published: (2023)

Stabilization Analysis and Mode Recognition of Kerosene Supersonic Combustion: A Deep Learning Approach Based on Res-CNN-beta-VAE
by: Xu, Weiming, et al.
Published: (2025)

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation
by: Wang, Haixin, et al.
Published: (2025)

Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
by: de Aguiar, Diego A., et al.
Published: (2024)

Data-driven low-dimensional model of a sedimenting flexible fiber
by: Fox, Andrew J, et al.
Published: (2024)

Data-driven Mori-Zwanzig modeling of Lagrangian particle dynamics in turbulent flows
by: de Wit, Xander, et al.
Published: (2025)

DamFormer: Generalizing Morphologies in Dam Break Simulations Using Transformer Model
by: Mul, Zhaoyang, et al.
Published: (2024)

Flash Freeze--Thaw Phenomenon in Sprayed Evaporating Micrometer Droplets
by: Wang, Junshi, et al.
Published: (2026)

SuperWing: a comprehensive transonic wing dataset for data-driven aerodynamic design
by: Yang, Yunjia, et al.
Published: (2025)

A Dynamic Droplet Breakup Model for Eulerian-Lagrangian Simulation of Liquid-fueled Detonation
by: Wang, Wenhao, et al.
Published: (2024)

Machine Learning Optimized Approach for Parameter Selection in MESHFREE Simulations
by: Banerjee, Paulami, et al.
Published: (2024)

Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation
by: Kohl, Georg, et al.
Published: (2023)

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
by: Ohana, Ruben, et al.
Published: (2024)

Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessment
by: Garnier, Paul, et al.
Published: (2025)

From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
by: Lienen, Marten, et al.
Published: (2023)

Hybrid Neural-MPM for Interactive Fluid Simulations in Real-Time
by: Xu, Jingxuan, et al.
Published: (2025)

Deep Learning-based Algebraic Reynolds Stress Closures for RANS Simulations of Turbulent Flows
by: Dehtyriov, Daniel, et al.
Published: (2026)

Machine Learning Techniques for Data Reduction of CFD Applications
by: Lee, Jaemoon, et al.
Published: (2024)

Learned Coarse Models for Efficient Turbulence Simulation
by: Stachenfeld, Kimberly, et al.
Published: (2021)

Reducing Spatial Discretization Error on Coarse CFD Simulations Using an OpenFOAM-Embedded Deep Learning Framework
by: Gonzalez-Sieiro, Jesus, et al.
Published: (2024)

On Free Moving Micron-Sized Droplet-Particle Collisions
by: Srivastava, Tushar, et al.
Published: (2026)

HFNO: an interpretable data-driven decomposition strategy for turbulent flows
by: Cayuela, Marco, et al.
Published: (2025)

Equation-informed data-driven identification of flow budgets and dynamics
by: Sevryugina, Nataliya, et al.
Published: (2024)

Coupling Machine Learning Local Predictions with a Computational Fluid Dynamics Solver to Accelerate Transient Buoyant Plume Simulations
by: Caron, Clément, et al.
Published: (2024)

Inpainting physics: self-supervised learning for context-driven fluid simulation
by: Weidner, Jonas, et al.
Published: (2026)

Smart navigation of a gravity-driven glider with adjustable centre-of-mass
by: Jiang, X., et al.
Published: (2025)

Uncertainty Quantification for Multi-fidelity Simulations
by: Kumar, Swapnil
Published: (2025)

Generalizable data-driven turbulence closure modeling on unstructured grids with differentiable physics
by: Kim, Hojin, et al.
Published: (2023)

Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network
by: Gu, Yuxuan, et al.
Published: (2024)

ConvNet-Based Prediction of Droplet Collision Dynamics in Microchannels
by: Mamun, SM Abdullah Al, et al.
Published: (2024)

Optimal Parallelization Strategies for Active Flow Control in Deep Reinforcement Learning-Based Computational Fluid Dynamics
by: Jia, Wang, et al.
Published: (2024)

Adaptive Diffusion Posterior Sampling for Data and Model Fusion of Complex Nonlinear Dynamical Systems
by: Chakraborty, Dibyajyoti, et al.
Published: (2026)

OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics
by: Zhang, Rui, et al.
Published: (2025)

Neural ensemble Kalman filter: Data assimilation for compressible flows with shocks
by: Zhou, Xu-Hui, et al.
Published: (2026)

The compressible Neural Particle Method for Simulating Compressible Viscous Fluid Flows
by: Shibukawa, Masato, et al.
Published: (2025)

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
by: Garnier, Paul, et al.
Published: (2025)

GIMLET: Generalizable and Interpretable Model Learning through Embedded Thermodynamics
by: Shiratori, Suguru, et al.
Published: (2025)

Physics-Guided Machine Learning for Uncertainty Quantification in Turbulence Models
by: Chu, Minghan, et al.
Published: (2025)

LAViG-FLOW: Latent Autoregressive Video Generation for Fluid Flow Simulations
by: De Pellegrini, Vittoria, et al.
Published: (2026)

A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling
by: Helwig, Jacob, et al.
Published: (2025)