Open Access
2016 Identifying turbulent structures through topological segmentation
Peer-Timo Bremer, Andrea Gruber, Janine Bennett, Attila Gyulassy, Hemanth Kolla, Jacqueline Chen, Ray Grout
Commun. Appl. Math. Comput. Sci. 11(1): 37-53 (2016). DOI: 10.2140/camcos.2016.11.37

Abstract

A new method of extracting vortical structures from a turbulent flow is proposed whereby topological segmentation of an indicator function scalar field is used to identify the regions of influence of the individual vortices. This addresses a long-standing challenge in vector field topological analysis: indicator functions commonly used produce a scalar field based on the local velocity vector field; reconstructing regions of influence for a particular structure requires selecting a threshold to define vortex extent. In practice, the same threshold is rarely meaningful throughout a given flow. By also considering the topology of the indicator field function, the characteristics of vortex strength and extent can be separated and the ambiguity in the choice of the threshold reduced. The proposed approach is able to identify several types of vortices observed in a jet in cross-flow configuration simultaneously where no single threshold value for a selection of common indicator functions appears able to identify all of these vortex types.

Citation

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Peer-Timo Bremer. Andrea Gruber. Janine Bennett. Attila Gyulassy. Hemanth Kolla. Jacqueline Chen. Ray Grout. "Identifying turbulent structures through topological segmentation." Commun. Appl. Math. Comput. Sci. 11 (1) 37 - 53, 2016. https://doi.org/10.2140/camcos.2016.11.37

Information

Received: 2 October 2014; Revised: 17 September 2015; Accepted: 18 October 2015; Published: 2016
First available in Project Euclid: 16 November 2017

zbMATH: 1326.76047
MathSciNet: MR3422853
Digital Object Identifier: 10.2140/camcos.2016.11.37

Subjects:
Primary: 65D18 , 68U05 , 76-02
Secondary: 68U10 , 76F40 , 76F65

Keywords: segmentation , topology , turbulence , vortex identification

Rights: Copyright © 2016 Mathematical Sciences Publishers

Vol.11 • No. 1 • 2016
MSP
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