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Computational fluid dynamics models based on Reynolds-averaged Navier--Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant…

流体动力学 · 物理学 2019-10-04 Heng Xiao , Jin-Long Wu , Sylvain Laizet , Lian Duan

We study the transport of self-propelled particles in dynamic complex environments. To obtain exact results, we introduce a model of run-and-tumble particles (RTPs) moving in discrete time on a $d$-dimensional cubic lattice in the presence…

We describe a new hybrid framework to model non-thermal spectral signatures from highly energetic particles embedded in a large-scale classical or relativistic MHD flow. Our method makes use of \textit{Lagrangian} particles moving through…

高能天体物理现象 · 物理学 2018-10-17 Bhargav Vaidya , Andrea Mignone , Gianluigi Bodo , Paola Rossi , Silvano Massaglia

We present an algorithm for simulating the equations of ideal magnetohydrodynamics and other systems of differential equations on an unstructured set of points represented by sample particles. Local, third-order, least-squares, polynomial…

天体物理仪器与方法 · 物理学 2015-05-30 Jason L. Maron , Colin P. McNally , Mordecai-Mark Mac Low

Multiscale organization is a hallmark of fluid turbulence in aerospace, energy, and transport systems. While quantum computing promises exponential speedups for solving the evolution equations governing flow fields, this potential is…

量子物理 · 物理学 2026-05-08 Zhaoyuan Meng , Xiao-Ming Zhang , Xiao Yuan , Yue Yang

Detailed data describing the motion of a rigid sphere settling in unperturbed fluid is generated by means of highly-accurate spectral/spectral-element simulations with the purpose of serving as a future benchmark case. A single…

流体动力学 · 物理学 2013-11-26 Markus Uhlmann , Jan Dusek

This study presents an innovative direct numerical simulation approach for complex particle systems with irregular shapes and large numbers. Using partially saturated methods, it accurately models arbitrary shapes, albeit at considerable…

流体动力学 · 物理学 2024-07-23 J. E. Marquardt , N. Hafen , M. J. Krause

The laminar-to-turbulent transition remains a fundamental and enduring challenge in fluid mechanics. Its complexity arises from the intrinsic nonlinearity and extreme sensitivity to external disturbances. This transition is critical in a…

流体动力学 · 物理学 2026-01-07 Wenhui Chang , Hongyuan Hu , Youcheng Xi , Markus Kloker , Honghui Teng , Jie Ren

Our ability to numerically model and understand the complex flow behavior of solid-bearing suspensions has increased significantly over the last couple of years, partly due to direct numerical simulations that compute flow around individual…

计算物理 · 物理学 2019-03-21 Zhipeng Qin , Kali Alison , Jenny Suckale

In order to model astrophysical environments characterized by radial stratification, such as supernova remnants or expanding superbubbles; correctly understanding the transport of non-thermal particles in astrophysical plasmas is essential.…

高能天体物理现象 · 物理学 2026-04-22 José María García-Morillo , Stefano Menchiari , Rubén López-Coto

Turbulent fluid flows are among the most computationally demanding problems in science, requiring enormous computational resources that become prohibitive at high flow speeds. Physics-informed neural networks (PINNs) represent a radically…

机器学习 · 计算机科学 2025-10-14 Sifan Wang , Shyam Sankaran , Xiantao Fan , Panos Stinis , Paris Perdikaris

A Skeleton-stabilized ImmersoGeometric Analysis technique is proposed for incompressible viscous flow problems with moderate Reynolds number. The proposed formulation fits within the framework of the finite cell method, where essential…

An accurate prediction of the translational and rotational motion of particles suspended in a fluid is only possible if a complete set of correlations for the force coefficients of fluid-particle interaction is known. The present study is…

流体动力学 · 物理学 2020-09-24 Martyna Minakowska , Thomas Richter , Sebastian Sager

The transport of heat and particles in the relatively collisional edge regions of magnetically confined plasmas is a scientifically challenging and technologically important problem. Understanding and predicting this transport requires the…

等离子体物理 · 物理学 2017-04-26 Ben Dudson , Jarrod Leddy

A substantial number of algorithms exists for the simulation of moving particles suspended in fluids. However, finding the best method to address a particular physical problem is often highly non-trivial and depends on the properties of the…

软凝聚态物质 · 物理学 2015-02-10 Jens Harting , Stefan Frijters , Marco Ramaioli , Martin Robinson , Dietrich E. Wolf , Stefan Luding

The dynamics of heavy particles suspended in turbulent flows is of fundamental importance for a wide range of questions in astrophysics, atmospheric physics, oceanography, and technology. Laboratory experiments and numerical simulations…

流体动力学 · 物理学 2016-09-21 K. Gustavsson , B. Mehlig

The study of viscous fluid flow coupled with rigid or deformable solids has many applications in biological and engineering problems, e.g., blood cell transport, drug delivery, and particulate flow. We developed a partitioned approach to…

流体动力学 · 物理学 2018-05-24 Jifu Tan , Talid Sinno , Scott Diamond

A model for the pseudo-turbulent Reynolds stress tensor in compressible flows through monodisperse particle clouds is developed based on data from particle resolved numerical simulations. This model extends previous models for the…

流体动力学 · 物理学 2025-05-09 Andreas Nygård Osnes , Magnus Vartdal

Turbulent plane-Couette flow suspended with finite-size spheroidal particles is studied using fully particle-resolved direct numerical simulations. The effects of particle aspect ratio on turbulent arguments and particle statistics are…

流体动力学 · 物理学 2023-11-06 Cheng Wang , Linfeng Jiang , Chao Sun

Lagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, bio-fluids, atmosphere, oceans, and astrophysics. Despite exceptional theoretical,…

流体动力学 · 物理学 2024-04-30 Tianyi Li , Luca Biferale , Fabio Bonaccorso , Martino Andrea Scarpolini , Michele Buzzicotti