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Detection of passive scalar interface directly from PIV particle images in inhomogeneous turbulent flows.

Gan, L. (2016) 'Detection of passive scalar interface directly from PIV particle images in inhomogeneous turbulent flows.', Flow, turbulence and combustion., 97 (1). pp. 141-170.

Abstract

This article proposes a technique to estimate the cross-sectional scalar interface (outer boundary) in an inhomogeneous turbulent flow from a conditioned particle image velocimetry (PIV) experiment, which is suitable for medium to high Reynolds numbers. The scalar interface is estimated directly by using conditioned PIV particle images which have distinguishably high particle seeding density in the area of interest, whereas conventionally in water based experiments, scalar interface is often determined from planar laser induced fluorescence (PLIF) or equivalent dye images. By comparing quantities in the vicinity of this scalar interface, it also shows that in terms of separate turbulent and non-turbulent regions, this technique could also replace the function of PLIF images in water experiments, with slightly lower spatial resolution. At the same time, if velocity information is also required simultaneously then the cost of a separate camera-laser system can be saved. The effect of particle field inhomogeneity on the PIV accuracy can be well reduced to an insignificant level by an image local normalisation treatment. This article shows that the interfacial layer could be detected fairly accurately by enhancing the particle images by wavelet based thresholding methods. The degree of detection accuracy is quantified by synthetic particle image analyses, where a scalar interface can be artificially pre-defined. The proposed technique is tested in two water based experiments but is expected to be particularly useful in gas-phase based experiments or some combustion applications, where liquid-phase dye cannot be applied.

Item Type:Article
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1007/s10494-015-9691-4
Publisher statement:© The Author(s) 2016. This article is published with open access at Springerlink.com
Date accepted:25 November 2015
Date deposited:08 March 2016
Date of first online publication:08 March 2016
Date first made open access:06 April 2016

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