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A new Lagrangian particle method for solving Euler equations for compressible inviscid fluid or gas flows is proposed. Similar to smoothed particle hydrodynamics (SPH), the method represents fluid cells with Lagrangian particles and is…

数值分析 · 数学 2016-03-21 Hsin-Chiang Chen , Roman Samulyak , Wei Li

We make use of the Lagrangian description of fluid motion to highlight certain features in the context of spacetime geometry as emergent phenomena in fluid systems. We find by using Lagrangian Perturbation Theory (LPT), that not all kind of…

广义相对论与量子宇宙学 · 物理学 2019-10-01 Satadal Datta

Reconstructing 3D fluid velocity fields from sparse 2D video observations is a highly ill-posed inverse problem, demanding both transport consistency with observed motion and physical validity under fluid laws. Existing methods typically…

图形学 · 计算机科学 2026-05-12 Ningxiao Tao , Baoquan Chen , Mengyu Chu

The aim of this paper is to discuss potential advances in PET kinetic models and direct reconstruction of kinetic parameters. As a prominent example we focus on a typical task in perfusion imaging and derive a system of…

最优化与控制 · 数学 2014-11-20 Louise Reips , Martin Burger , Ralf Engbers

A novel experimental platform is developed to investigate the dynamics of inertial particles (micro-droplets) in air turbulence. The goal is to observe particle collision and coalescence in turbulent flows, focusing on its impact on the…

流体动力学 · 物理学 2026-03-12 L. Fu , J. Feng , Y. Chen , F. Gong , X. Meng , E. -W. Saw

As most mathematically justifiable Lagrangian coherent structure detection methods rely on spatial derivatives, their applicability to sparse trajectory data has been limited. For experimental fluid dynamicists and natural scientists…

流体动力学 · 物理学 2024-11-20 Nikolas O. Aksamit , Alex P. Encinas-Bartos , George Haller , David E. Rival

The particle proper orthogonal decomposition (PPOD) is demonstrated on cases of particle flows in decaying homogeneous isotropic turbulence. Data is generated through one-way coupled simulations, where particle positions and velocities are…

流体动力学 · 物理学 2022-05-30 Martin Schiødt , Azur Hodzic , Fabien Evrard , Berend van Wachem , Clara M. Velte

We report a novel experimental technique that measures simultaneously in three dimensions the trajectories, the translation, and the rotation of finite size inertial particles together with the turbulent flow. The flow field is analyzed by…

流体动力学 · 物理学 2012-12-24 Simon Klein , Mathieu Gibert , Antoine Bérut , Eberhard Bodenschatz

Volume-resolving imaging techniques are rapidly advancing progress in experimental fluid mechanics. However, reconstructing the full and structured Eulerian velocity and pressure fields from sparse and noisy particle tracks obtained…

流体动力学 · 物理学 2023-05-17 Patricio Clark Di Leoni , Karuna Agarwal , Tamer Zaki , Charles Meneveau , Joseph Katz

Flow visualization technologies such as particle tracking velocimetry (PTV) are broadly used in understanding the all-pervasiveness three-dimensional (3D) turbulent flow from nature and industrial processes. Despite the advances in 3D…

流体动力学 · 物理学 2022-11-01 Jiaming Liang , Chao Xu , Shengze Cai

Particle tracking in turbulent flows is fundamental to the study of the transport of tracers, inertial particles or even active objects in space and time, i.e. the Lagrangian frame of reference. It provides experimental tests of theoretical…

流体动力学 · 物理学 2024-04-08 Christian Küchler , Antonio Ibanez Landeta , Jan Molacek , Eberhard Bodenschatz

Obtaining system parameters and reconstructing the full flow state from limited velocity observations using conventional fluid dynamics solvers can be prohibitively expensive. Here we employ machine learning algorithms to overcome the…

流体动力学 · 物理学 2024-10-17 Vladimir Parfenyev , Mark Blumenau , Ilia Nikitin

We investigate the response of large inertial particle to turbulent fluctuations in a inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters…

流体动力学 · 物理学 2016-04-20 Nathanaël Machicoane , Romain Volk

A particle tracking velocimetry apparatus is presented that is capable of measuring three-dimensional particle trajectories across large volumes, of the order of several meters, during natural snowfall events. Field experiments, aimed at…

流体动力学 · 物理学 2023-04-12 Nathaniel Bristow , Jiaqi Li , Peter Hartford , Michele Guala , Jiarong Hong

We present in this article a novel Lagrangian measurement technique: an instrumented particle which continuously transmits the force/acceleration acting on it as it is advected in a flow. We develop signal processing methods to extract…

流体动力学 · 物理学 2015-06-11 Robert Zimmermann , Lionel Fiabane , Yoann Gasteuil , Romain Volk , Jean-François Pinton

We introduce Lagrangian Flow Networks (LFlows) for modeling fluid densities and velocities continuously in space and time. By construction, the proposed LFlows satisfy the continuity equation, a PDE describing mass conservation in its…

机器学习 · 计算机科学 2023-12-15 F. Arend Torres , Marcello Massimo Negri , Marco Inversi , Jonathan Aellen , Volker Roth

We introduce a new Lagrangian particle tracking algorithm that tracks particles in three dimensions to separations between trajectories approaching contact. The algorithm also detects low Weber number binary collisions that result in…

流体动力学 · 物理学 2020-07-15 Reece Vincent Kearney , Gregory Paul Bewley

There are several approaches to describe flows with particles e.g. Lattice-Gas Automata (LGA), Lattice-Boltzmann method (LBM) or smoothed particle hydrodynamics (SPH). These approaches do not use fixed grids on which the Navier-Stokes…

流体动力学 · 物理学 2008-02-27 B. Ivancic

Understanding, quantifying and controlling transport and mixing processes are central in the study of fluid flows. Many different Lagrangian approaches have been proposed for detecting organizing flow structures that determine material…

流体动力学 · 物理学 2026-04-17 Anna Klünker , Alexandra von Kameke , Kathrin Padberg-Gehle

In this paper, we present a comprehensive evaluation to establish a robust and efficient framework for Lagrangian-based particle tracing using deep neural networks (DNNs). Han et al. (2021) first proposed a DNN-based approach to learn…

图形学 · 计算机科学 2024-05-16 Mengjiao Han , Jixian Li , Sudhanshu Sane , Shubham Gupta , Bei Wang , Steve Petruzza , Chris R. Johnson