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We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in micro-fluidic devices. The system is…

Soft Condensed Matter · Physics 2017-06-07 T. Darnige , N. Figueroa-Morales , P. Bohec , A. Lindner , E. Clément

Borrowing terminology from fluid mechanics, the concepts of {\em Eulerian} and {\em Lagrangian optical flow sensing} are introduced. Eulerian optical flow sensing assumes that each photoreceptor in the camera or eye can instantaneously…

Systems and Control · Electrical Eng. & Systems 2021-03-02 John Baillieul , Feiyang Kang

In the Eulerian approach, the motion of an incompressible fluid is usually described by the velocity field which is given by the Navier--Stokes system. The velocity field generates a flow in the space of volume-preserving diffeomorphisms.…

Analysis of PDEs · Mathematics 2015-06-19 Vahagn Nersesyan

Detecting the transition from laminar to turbulent flow in particulate pipe systems remains a complex issue in fluid dynamics, often requiring sophisticated and costly experimental apparatus. This research presents an innovative streak…

Fluid Dynamics · Physics 2025-01-06 Rishav Raj , Abhiram Thiruthummal , Alban Potherat

Lagrangian averaging plays an important role in the analysis of wave--mean-flow interactions and other multiscale fluid phenomena. The numerical computation of Lagrangian means, e.g. from simulation data, is however challenging. Typical…

Fluid Dynamics · Physics 2023-04-26 Hossein A. Kafiabad , Jacques Vanneste

We present an Eulerian vortex method based on the theory of flow maps to simulate the complex vortical motions of incompressible fluids. Central to our method is the novel incorporation of the flow-map transport equations for line elements,…

Graphics · Computer Science 2024-09-17 Sinan Wang , Yitong Deng , Molin Deng , Hong-Xing Yu , Junwei Zhou , Duowen Chen , Taku Komura , Jiajun Wu , Bo Zhu

Granular gases are commonly characterized through their velocity distribution, which provides access to the granular temperature. In experiments, velocity distributions are typically obtained by particle tracking, which however becomes…

Lagrangian averaging is a valuable tool for the analysis and modelling of multiscale processes in fluid dynamics. The numerical computation of Lagrangian (time) averages from simulation data is challenging, however. It can be carried out by…

Fluid Dynamics · Physics 2024-12-23 Abhijeet Minz , Lois E. Baker , Hossein A. Kafiabad , Jacques Vanneste

We study the Lagrangian dynamics of passive tracers in a simple model of a driven two-dimensional vortex resembling real-world geophysical flow patterns. Using a discrete approximation of the system's transfer operator, we construct a…

Chaotic Dynamics · Physics 2017-04-05 Michael Lindner , Reik V. Donner

We have developed a simulation technique of multiscale Lagrangian fluid dynamics to tackle hierarchical problems relating to historical dependency of polymeric fluid. We investigate flow dynamics of dilute polymeric fluid by using the…

Computational Physics · Physics 2010-04-09 Takahiro Murashima , Takashi Taniguchi

The random intensity of noise approach to one-dimensional Laval-Dubrulle-Nazarenko type model having deductive support from the three-dimensional Navier-Stokes equation is used to describe Lagrangian acceleration statistics of a fluid…

Statistical Mechanics · Physics 2007-05-23 A. K. Aringazin

Lagrangian statistics of passive tracers in rotating turbulence is investigated by Particle Tracking Velocimetry. A confined and steadily-forced turbulent flow is subjected to five different rotation rates. The PDFs of the velocity…

Fluid Dynamics · Physics 2013-07-24 Lorenzo Del Castello , Herman J. H. Clercx

We present a model for the Lagrangian dynamics of inertial particles in a compressible flow, where fluid velocity gradients are modelled by a telegraph noise. The model allows for an analytic investigation of the role of time correlation of…

Chaotic Dynamics · Physics 2009-10-06 G. Falkovich , S. Musacchio , L. Piterbarg , M. Vucelja

A new kind of Lagrangian diagnostic family is proposed and a specific form of it is suggested for characterizing mixing: the maximal extent of a trajectory (MET). It enables the detection of coherent structures and their dynamics in two-…

Chaotic Dynamics · Physics 2018-04-10 Ruty Mundel , Erick Fredj , Hezi Gildor , Vered Rom-Kedar

We show that Lagrangian measurements in active turbulence bear imprints of turbulent and anomalous streaky hydrodynamics leading to a self-selection of persistent trajectories - Levy walks - over diffusive ones. This emergent dynamical…

Fluid Dynamics · Physics 2022-08-26 Rahul K. Singh , Siddhartha Mukherjee , Samriddhi Sankar Ray

We describe a new computational method for the numerically stable particle-based simulation of open-boundary flows, including volume conserving chemical reactions. The novel method is validated for the case of heterogeneous catalysis…

Adaptation and Self-Organizing Systems · Physics 2020-10-09 Sebastian Mühlbauer , Severin Strobl , Thorsten Pöschel

This article describes two independent developments aimed at improving the Particle Tracking Method for measurements of flow or particle velocities. First, a stereoscopic multicamera calibration method that does not require any optical…

We present Lagrangian one-particle statistics from the Risoe PTV experiment of a turbulent flow. We estimate the Lagrangian Kolmogorov constant $C_0$ and find that it is affected by the large scale inhomogeneities of the flow. The pdf of…

Fluid Dynamics · Physics 2007-05-23 J. Berg

Particle Flow Filters perform the measurement update by moving particles to a different location rather than modifying the particles' weight based on the likelihood. Their movement (flow) is dictated by a drift term, which continuously…

Computational Engineering, Finance, and Science · Computer Science 2025-07-04 Simone Servadio

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…

Graphics · Computer Science 2024-05-16 Mengjiao Han , Jixian Li , Sudhanshu Sane , Shubham Gupta , Bei Wang , Steve Petruzza , Chris R. Johnson
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