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We give an algorithmic introduction to Lagrangian coherent structures (LCSs) using a newly developed computational engine, LCS Tool. LCSs are most repelling, attracting and shearing material lines that form the centerpieces of observed…

Chaotic Dynamics · Physics 2016-04-12 K. Onu , F. Huhn , G. Haller

The computation of Lagrangian coherent structures (LCS) has established itself as a prominent means to reveal significant geometric structures in time-dependent vector fields. Their characterization, however, requires the selection of a…

Fluid Dynamics · Physics 2022-03-23 Zi'ang Ding , Xavier Tricoche

Lagrangian Coherent Structures (LCS) are flow features which are defined to objectively characterize complex fluid behavior over a finite time regardless of the orientation of the observer. Fluidic applications of LCS include geophysical,…

Fluid Dynamics · Physics 2023-10-18 Tanner D. Harms , Steven L. Brunton , Beverley J. McKeon

To facilitate the understanding and to quantitatively assess the material transport in fluids, a modern characterisation method has emerged in fluid dynamics in the last decades footed in dynamical systems theory. It allows to examine the…

Lagrangian coherent structures (LCS) in fluid flows appear as co-dimension one ridges of the finite time Lyapunov exponent (FTLE) field. In three- dimensions this means two-dimensional ridges. A fast algorithm is presented here to locate…

Fluid Dynamics · Physics 2012-02-24 Doug Lipinski , Kamran Mohseni

Lagrangian coherent structures (LCSs) are material surfaces that shape finite-time tracer patterns in flows with arbitrary time dependence. Depending on their deformation properties, elliptic and hyperbolic LCSs have been identified from…

Dynamical Systems · Mathematics 2016-11-23 David Oettinger , George Haller

We present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number, as is the case in many fluid mechanics applications of practical interest. The method, based on principles…

Fluid Dynamics · Physics 2017-03-08 Kristy L. Schlueter-Kuck , John O. Dabiri

Many complex flows such as those arising from ocean plastics in geophysics or moving cells in biology are characterized by sparse and noisy trajectory datasets. We introduce techniques for identifying Lagrangian Coherent Structures (LCSs)…

Fluid Dynamics · Physics 2022-09-21 Saviz Mowlavi , Mattia Serra , Enrico Maiorino , L Mahadevan

We present a method for identifying the coherent structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data is available. The method, based on techniques in spectral graph theory, uses…

Fluid Dynamics · Physics 2017-10-11 Kristy L. Schlueter-Kuck , John O. Dabiri

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…

Fluid Dynamics · Physics 2026-04-17 Anna Klünker , Alexandra von Kameke , Kathrin Padberg-Gehle

Current supercomputers often have a heterogeneous architecture using both CPUs and GPUs. At the same time, numerical simulation tasks frequently involve multiphysics scenarios whose components run on different hardware due to multiple…

Computational Engineering, Finance, and Science · Computer Science 2024-12-10 Samuel Kemmler , Christoph Rettinger , Ulrich Rüde , Pablo Cuéllar , Harald Köstler

We consider the relationship between Eulerian modal decompositions and Lagrangian coherent structures (LCSs). The model sensitivity framework developed by Kasz\'as and Haller (2020) is used to express data-driven modal representations of…

Fluid Dynamics · Physics 2025-12-24 Morgan R. Jones , Charles Klewicki , Oliver Khan , Steven L. Brunton , Mitul Luhar

We explore the application of the reference map technique, originally developed for the Eulerian simulation of solid mechanics, in Lagrangian kinematics of fluid flows. Unlike traditional methods based on explicit particle tracking, the…

Fluid Dynamics · Physics 2024-12-04 Imran Hayat , Ryan T. Black , George Ilhwan Park

We present \texttt{lcg\_plus}, an open-source Python library for the simulation of continuous-variable quantum circuits with both generaldyne and photon-number-resolving detector capabilities. Our framework merges the linear combination of…

Quantum Physics · Physics 2025-08-11 Olga Solodovnikova , Ulrik L. Andersen , Jonas S. Neergaard-Nielsen

Turbulence and chaos play a fundamental role in stellar convective zones through the transportof particles, energy and momentum, and in fast dynamos, through the stretching, twisting and folding of magnetic flux tubes. A particularly…

Solar and Stellar Astrophysics · Physics 2015-05-20 Erico L. Rempel , Abraham C. -L. Chian , Axel Brandenburg

We describe a new method for computing coherent Lagrangian vortices in two-dimensional flows according to any of the following approaches: black-hole vortices [Haller & Beron-Vera, 2013], objective Eulerian Coherent Structures (OECSs)…

Fluid Dynamics · Physics 2020-06-23 Daniel Karrasch , Nathanael Schilling

A numerical model and parallel software for 3D simulations of granular flows have been developed based on the Lagrangian particle (LP) method [R.Samulyak, X. Wang, H.-C. Chen, Lagrangian particle method for compressible fluid dynamics, J.…

Computational Physics · Physics 2022-06-29 Mario Zepeda , Roman Samulyak

We review and test twelve different approaches to the detection of finite-time coherent material structures in two-dimensional, temporally aperiodic flows. We consider both mathematical methods and diagnostic scalar fields, comparing their…

Accurate prediction of Lagrangian trajectories in turbulent flow remains challenging due to limited temporal information in transport functions. This paper shows that surrounding coherent motions sharing the same dynamics carry enough…

Fluid Dynamics · Physics 2026-05-07 Ali R Khojasteh , Dominique Heitz

A computational fluid dynamics (CFD) simulation framework for fluid-flow prediction is developed on the Tensor Processing Unit (TPU) platform. The TPU architecture is featured with accelerated dense matrix multiplication, large high…

Computational Physics · Physics 2022-03-02 Qing Wang , Matthias Ihme , Yi-Fan Chen , John Anderson
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