中文
相关论文

相关论文: Machine-learning heat flux closure for multi-momen…

200 篇论文

Solving fluid dynamics equations often requires the use of closure relations that account for missing microphysics. For example, when solving equations related to fluid dynamics for systems with a large Reynolds number, sub-grid effects…

计算物理 · 物理学 2023-06-21 Archis S. Joglekar , Alexander G. R. Thomas

Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based…

计算物理 · 物理学 2019-12-09 Cristina White , Daniela Ushizima , Charbel Farhat

Thermal fluid processes are inherently multi-physics and multi-scale, involving mass-momentum-energy transport phenomena. Thermal fluid simulation (TFS) is based on solving conservative equations, for which - except for "first-principle"…

流体动力学 · 物理学 2018-11-07 Chih-Wei Chang , Nam T. Dinh

Three-dimensional numerical simulations of decaying turbulence in a magnetized plasma are performed using a so-called FLR-Landau fluid model which incorporates linear Landau damping and finite Larmor radius (FLR) corrections. It is shown…

等离子体物理 · 物理学 2015-05-30 P. Hunana , D. Laveder , T. Passot , P. L. Sulem , D. Borgogno

We investigate the dynamics of plasma-based acceleration processes with collisionless particle dynamics and non negligible thermal effects. We aim at assessing the applicability of fluid-like models, obtained by suitable closure assumptions…

等离子体物理 · 物理学 2024-09-17 Daniele Simeoni , Andrea Renato Rossi , Gianmarco Parise , Fabio Guglietta , Mauro Sbragaglia

This study introduces a hybrid fluid simulation approach that integrates generative diffusion models with physics-based simulations, aiming at reducing the computational costs of flow simulations while still honoring all the physical…

We present a novel method for guaranteeing linear momentum in learned physics simulations. Unlike existing methods, we enforce conservation of momentum with a hard constraint, which we realize via antisymmetrical continuous convolutional…

机器学习 · 计算机科学 2022-11-03 Lukas Prantl , Benjamin Ummenhofer , Vladlen Koltun , Nils Thuerey

The flow-induced vibration of bluff bodies is an important problem of many marine, civil, or mechanical engineers. In the design phase of such structures, it is vital to obtain good predictions of the fluid forces acting on the structure.…

系统与控制 · 计算机科学 2018-04-24 Jan Decuyper , Tim De Troyer , Mark Runacres , Koen Tiels , Johan Schoukens

A Landau fluid model for a collisionless electron-proton magnetized plasma, that accurately reproduces the dispersion relation and the Landau damping rate of all the magnetohydrodynamic waves, is presented. It is obtained by an accurate…

等离子体物理 · 物理学 2010-04-02 P. Goswami , T. Passot , P. L. Sulem

Accurate reduced models of turbulence are desirable to facilitate the optimization of magnetic-confinement fusion reactor designs. As a first step toward higher-dimensional turbulence applications, we use reservoir computing, a…

等离子体物理 · 物理学 2025-10-21 Nathaniel Barbour , William Dorland , Ian G. Abel , Matt Landreman

Incorporation of kinetic effects such as Landau damping into a fluid framework was pioneered by Hammett and Perkins PRL 1990, by obtaining closures of the fluid hierarchy, where the gyrotropic heat flux fluctuations or the deviation of the…

等离子体物理 · 物理学 2018-10-17 P. Hunana , G. P. Zank , M. Laurenza , A. Tenerani , G. M. Webb , M. L. Goldstein , M. Velli , L. Adhikari

Modeling the mechanics of fluid in complex scenes is vital to applications in design, graphics, and robotics. Learning-based methods provide fast and differentiable fluid simulators, however most prior work is unable to accurately model how…

机器学习 · 计算机科学 2023-09-12 Arjun Mani , Ishaan Preetam Chandratreya , Elliot Creager , Carl Vondrick , Richard Zemel

The inclusion of kinetic effects into fluid models has been a long standing problem in magnetic reconnection and plasma physics. Generally the pressure tensor is reduced to a scalar which is an approximation used to aid in the modeling of…

等离子体物理 · 物理学 2023-03-15 John Donaghy , Kai Germaschewski

Recently, computational modeling has shifted towards the use of deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many applications like design optimization and real-time control by…

流体动力学 · 物理学 2021-10-11 Suraj Pawar , Omer San , Prakash Vedula , Adil Rasheed , Trond Kvamsdal

Fluid simulation is an important research topic in computer graphics (CG) and animation in video games. Traditional methods based on Navier-Stokes equations are computationally expensive. In this paper, we treat fluid motion as point cloud…

计算机视觉与模式识别 · 计算机科学 2025-01-07 Yu Chen , Shuai Zheng , Nianyi Wang , Menglong Jin , Yan Chang

We propose a neural physics system for real-time, interactive fluid simulations. Traditional physics-based methods, while accurate, are computationally intensive and suffer from latency issues. Recent machine-learning methods reduce…

机器学习 · 计算机科学 2025-05-27 Jingxuan Xu , Hong Huang , Chuhang Zou , Manolis Savva , Yunchao Wei , Wuyang Chen

Modelling the sudden depressurisation of superheated liquids through nozzles is a challenge because the pressure drop causes rapid flash boiling of the liquid. The resulting jet usually demonstrates a wide range of structures, including…

流体动力学 · 物理学 2021-12-15 David Schmidt , Romit Maulik , Konstantinos G. Lyras

Kinetic simulations of collisionless plasmas are computationally challenging due to phase space mixing and filamentation, resulting in fine-scale velocity structures. This study compares three methods developed to reduce artifacts related…

等离子体物理 · 物理学 2025-03-21 Opal Issan , Oleksandr Chapurin , Oleksandr Koshkarov , Gian Luca Delzanno

Fast and stable fluid simulations are an essential prerequisite for applications ranging from computer-generated imagery to computer-aided design in research and development. However, solving the partial differential equations of…

机器学习 · 计算机科学 2021-03-03 Nils Wandel , Michael Weinmann , Reinhard Klein

Deep learning has shown great potential for modeling the physical dynamics of complex particle systems such as fluids. Existing approaches, however, require the supervision of consecutive particle properties, including positions and…

机器学习 · 计算机科学 2022-06-22 Shanyan Guan , Huayu Deng , Yunbo Wang , Xiaokang Yang