A method for measuring the dynamics of velocity vector fields in a turbulent flow using smoke image-visualization videos

Михеев, Н. И.; Dushin, N. S.

doi:10.1134/s0020441216060063

Cited by 55 publications

(6 citation statements)

References 6 publications

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“…The videos were recorded by a high-speed monochrome camera Fastec HiSpec in a light sheet in x0y plane (channel symmetry plane) and in the plane parallel to x0z at y = 4.5 mm (tangent to the cylinder generatrix). Instantaneous velocity vector fields in the cylinder wake were measured by SIV technique [6].…”

Section: Methodsmentioning

confidence: 99%

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Mechanism of transition to turbulence in a circular cylinder wake in a channel

et al. 2017

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Abstract. Transition to turbulence in the circular cylinder wake has been studied experimentally and numerically at growing Reynolds number. Good agreement of calculation results with the flow visualization and measurements of instantaneous vector fields of velocity and vorticity has been demonstrated. The growing Reynolds number is shown to make large-scale vortex generation onset move upstream. It also triggers the transition to 3D flow pattern in the cylinder wake. This process is accompanied by non-monotonous behavior of the profiles of velocity and its turbulent fluctuations at equal distances from the cylinder. Nonmonotonous behavior of the cylinder drag has been revealed for the Reynolds numbers ranging from 120 to 300.

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Section: Methodsmentioning

confidence: 99%

“…The other three instabilities had different wavelengths of 3D global modes. A number of authors note that flow turbulization around the cylinder is accompanied by the transition to 3D wake structure [6].…”

Section: Introductionmentioning

confidence: 99%

Mechanism of transition to turbulence in a circular cylinder wake in a channel

et al. 2017

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“…It is an optical measurement method. Articles [18,19] give a detailed description of the SIV method, estimation of its accuracy, and applicability to the measurement of various flow characteristics. The SIV method was chosen due to the peculiarities of the image-processing algorithm.…”

Section: Visualizationmentioning

confidence: 99%

Exact Solution for Viscoelastic Flow in Pipe and Experimental Validation

et al. 2022

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The development of analytical methods for viscoelastic fluid flows is challenging. Currently, this problem has been solved for particular cases of multimode differential rheological equations of media state (Giesekus, the exponential form of Phan-Tien-Tanner, eXtended Pom-Pom). We propose a parametric method that yields solutions without additional assumptions. The method is based on the parametric representation of the unknown velocity functions and the stress tensor components as a function of coordinate. Experimental flow visualization based on the SIV (smoke image velocimetry) method was carried out to confirm the obtained results. Compared to the Giesekus model, the experimental data are best predicted by the eXtended Pom-Pom model.

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“…The result of cross-correlation processing of such images can be used for a lower estimate of the gas velocity in the boundary layer. The smoke visualization method proposed at the Kazan Scientific Center of the Russian Academy of Sciences [132] is based on digital processing of smoke visualization video recorded on a light sheet. The gas flows are seeded by aerosol generators that follows the gas flow in the same way as in PIV, but due to their higher concentration, they appear in the image as not illuminated individual particles, but smoke with a continuous intensity.…”

Section: Pivmentioning

confidence: 99%

Methods for Panoramic Visualization and Digital Analysis of Thermophysical Flow Fields. A Review.

Znamenskaya¹

2021

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The paper presents a review of modern methods in the registration, processing, and analysis of dynamic processes in liquids, gases, plasmas, multiphase media, which are realized in researches and technology. The review author observes both the physical fundamentals of flow visualization and the basics of modern technologies for digital processing of recorded flow images. A brief analysis of the panoramic visualization methods progress history covers a period of one and a half centuries. In the works of the last decade, the focus is on the methods of computer processing, tools, technologies for analyzing and recognizing of panoramic thermophysical fields, which make it possible to obtain quantitative information about flows. The review contains an analysis of publications describing the main modern methods of visualization of flows: methods based on the phenomenon of refraction; electroluminescence; on digital tracing (particle image velocimetry), visualization of surface flows (PSP and TSP coatings, liquid crystals; oil coatings). Particular attention is paid to methods using crosscorrelation image processing algorithms. Those are: digital tracing (PIV), shadow background method (in English Background Oriented Schlieren -BOS), seedless shadow methods, thermographic PIV, velocity measurement in viscous coatings, micro, tomographic modifications of PIV, etc. The actual problem of digital data analyzing in a panoramic experiment is touched upon -the problem of big data. Examples of the machine learning use in the analysis of big data sets of shadow surveys are given. Some examples of numerical simulation data visualization (simulation of experimental flowfields) are considered.

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A method for measuring the dynamics of velocity vector fields in a turbulent flow using smoke image-visualization videos

Cited by 55 publications

References 6 publications

Mechanism of transition to turbulence in a circular cylinder wake in a channel

Mechanism of transition to turbulence in a circular cylinder wake in a channel

Exact Solution for Viscoelastic Flow in Pipe and Experimental Validation

Methods for Panoramic Visualization and Digital Analysis of Thermophysical Flow Fields. A Review.

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