Image de couverture de livre

Stabilizing the Maximal Entropy Moment Method for Rarefied Gas Dynamics at Single-Precision

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zheng, Candi, Yang, Wang, Chen, Shiyi
Format:	Preprint
Publié:	2023
Sujets:	Fluid Dynamics Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Shock-Aware Physics-Guided Fusion-DeepONet Operator for Rarefied Micro-Nozzle Flows
par: Roohi, Ehsan, et autres
Publié: (2025)

Learning Rarefied Gas Dynamics with Physics-Enforced Neural Networks
par: Roohi, Ehsan, et autres
Publié: (2025)

A Hybrid Gas-Kinetic Scheme and Discrete Velocity Method for Continuum and Rarefied Flows
par: Wu, Hangkong, et autres
Publié: (2026)

Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework
par: Zhang, Dashan, et autres
Publié: (2023)

A Particle Multi-Relaxation Bhatnagar-Gross-Krook Method for Rarefied Monatomic Gas Mixtures
par: Kim, Inchan, et autres
Publié: (2026)

Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression
par: Wang, Ding, et autres
Publié: (2024)

Physics-Informed Neural Networks for microflows: Rarefied Gas Dynamics in Cylinder Arrays
par: Tucny, Jean-Michel, et autres
Publié: (2025)

Extensions to the Navier-Stokes-Fourier Equations for Rarefied Transport: Variational Multiscale Moment Methods for the Boltzmann Equation
par: Baidoo, F. A., et autres
Publié: (2024)

Wetted-Area Minimum and Inlet-Outlet Reciprocity in Optimal Manifolds of Rarefied Gas Flows
par: Yuan, Ruifeng, et autres
Publié: (2025)

Adaptive Sampling for Hydrodynamic Stability
par: Singh, Anshima, et autres
Publié: (2025)

Method of data forward generation with partial differential equations for machine learning modeling in fluid mechanics
par: Chen, Ruilin
Publié: (2025)

LLM4Fluid: Large Language Models as Generalizable Neural Solvers for Fluid Dynamics
par: Xiao, Qisong, et autres
Publié: (2026)

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
par: Yang, Tianyue, et autres
Publié: (2026)

Towards Scalable One-Step Generative Modeling for Autoregressive Dynamical System Forecasting
par: Yang, Tianyue, et autres
Publié: (2026)

FlowPrecision: Advancing FPGA-Based Real-Time Fluid Flow Estimation with Linear Quantization
par: Ling, Tianheng, et autres
Publié: (2024)

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

Reservoir Computing with a Single Oscillating Gas Bubble: Emphasizing the Chaotic Regime
par: Abdel-Ghani, Hend, et autres
Publié: (2025)

Dynamic Feature-based Deep Reinforcement Learning for Flow Control of Circular Cylinder with Sparse Surface Pressure Sensing
par: Wang, Qiulei, et autres
Publié: (2023)

Efficient Collision Algorithms in DSMC for Rarefied Gas Dynamics: Markovian NTC-Pre-Scan and Bernoulli-Trial Schemes
par: Shoja-sani, Ahmad, et autres
Publié: (2025)

Model-Agnostic AI Framework with Explicit Time Integration for Long-Term Fluid Dynamics Prediction
par: Yang, Sunwoong, et autres
Publié: (2024)

AI-Accelerated Operator Learning Framework for Rarefied Microflows
par: Roohi, Ehsan
Publié: (2025)

Dimensionality Reduction and Dynamical Mode Recognition of Circular Arrays of Flame Oscillators Using Deep Neural Network
par: Xu, Weiming, et autres
Publié: (2023)

Physical Fidelity Reconstruction via Improved Consistency-Distilled Flow Matching for Dynamical Systems
par: Ma, Sicheng, et autres
Publié: (2026)

OmniFluids: Physics Pre-trained Modeling of Fluid Dynamics
par: Zhang, Rui, et autres
Publié: (2025)

CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics
par: Luo, Yining, et autres
Publié: (2023)

Optimal Parallelization Strategies for Active Flow Control in Deep Reinforcement Learning-Based Computational Fluid Dynamics
par: Jia, Wang, et autres
Publié: (2024)

Learning the Optimal Hydrodynamic Closure
par: Kogelbauer, Florian, et autres
Publié: (2025)

Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
par: Grozavescu, Rares, et autres
Publié: (2026)

DiffFluid: Plain Diffusion Models are Effective Predictors of Flow Dynamics
par: Luo, Dongyu, et autres
Publié: (2024)

Coupled Integral PINN for Discontinuity
par: Wang, Yeping, et autres
Publié: (2024)

The compressible Neural Particle Method for Simulating Compressible Viscous Fluid Flows
par: Shibukawa, Masato, et autres
Publié: (2025)

Data-Driven Computing Methods for Nonlinear Physics Systems with Geometric Constraints
par: Tong, Yunjin
Publié: (2024)

Inpainting Computational Fluid Dynamics with Deep Learning
par: Shu, Dule, et autres
Publié: (2024)

Predicting Flow Dynamics using Diffusion Models
par: Gachnang, Yannick, et autres
Publié: (2025)

Transported Memory Networks accelerating Computational Fluid Dynamics
par: Schulz, Matthias, et autres
Publié: (2025)

Global Description of Flutter Dynamics via Koopman Theory
par: Song, Jiwoo, et autres
Publié: (2025)

CoNFiLD-inlet: Synthetic Turbulence Inflow Using Generative Latent Diffusion Models with Neural Fields
par: Liu, Xin-Yang, et autres
Publié: (2024)

Contactless Precision Steering of Particles in a Fluid inside a Cube with Rotating Walls
par: Amoudruz, Lucas, et autres
Publié: (2025)

Neural SPH: Improved Neural Modeling of Lagrangian Fluid Dynamics
par: Toshev, Artur P., et autres
Publié: (2024)

Machine-learning-based multipoint optimization of fluidic injection parameters for improving nozzle performance
par: Yang, Yunjia, et autres
Publié: (2024)