Quantitative measurement of spatio-temporal heat transfer to a turbulent water pipe flow

Nakamura, Hajime; Shiibara, Naoki; Yamada, S.

doi:10.1016/j.ijheatfluidflow.2016.09.016

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…For this reason, many studies have investigated the role of coherent structures on scalar transport, both experimentally and computationally; Refs. [5][6][7][8][9][10][11][12] constitute a small sample from an extensive literature. These structures have also been analysed using different types of modal decomposition techniques.…”

Section: Introductionmentioning

confidence: 99%

Analysis of wall mass transfer in turbulent pipe flow combining extended proper orthogonal decomposition and Fukagata-Iwamoto-Kasagi identity

2022

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We combine extended proper orthogonal decomposition (EPOD) together with the Fukagata-Iwamoto-Kasagi (FIK) identity to quantify the role of individual coherent structures on the wall mass transfer in a turbulent pipe flow. Direct numerical simulation (DNS) at a Reynolds number of 5300 (based on bulk velocity) is performed with the passive scalar released at the pipe inlet. The proper orthogonal decomposition (POD) eigenvalues show that the scalar field can be described by a more compact set of modes compared to the velocity field, and that these modes are skewed towards

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Section: Introductionmentioning

confidence: 99%

Analysis of wall mass transfer in turbulent pipe flow combining extended proper orthogonal decomposition and Fukagata-Iwamoto-Kasagi identity

2022

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“…Of practical interest were the problems of monitoring and scanning the temperature field of the outer mixers walls during the flow of water and liquid metal coolants [77][78][79][80][81]. For impact jets, measurements of the spatial and temporal characteristics of a turbulent water flow were usually carried out through a thin metal wall (plate, foil) [82][83][84][85]. The averaged thermal fields obtained due to heat transfer of the investigated flow to a solid wall were recorded.…”

Section: Application Of Infrared Thermographymentioning

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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“…Nevertheless very few studies focus on the temporal variation of turbulent heat transfer at the wall and on the dynamical mechanism of turbulent heat transfer. Recent attempts have been performed experimentally by [5] thanks to the development of timeresolved heat transfer sensors [6,7]. Few studies are dealing with resolved numerical simulation of pipe flows heat transfer mostly due to the computational complexity associated with the cylindrical coordinate system and the corresponding numerical singularity along the symmetry line.…”

Section: Introductionmentioning

confidence: 99%

Extended proper orthogonal decomposition of non-homogeneous thermal fields in a turbulent pipe flow

Antoranz

Ianiro

Flores

et al. 2018

International Journal of Heat and Mass Transfer

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This manuscript analyzes the role of coherent structures in turbulent thermal transport in pipe flows. A Proper Orthogonal Decomposition (POD) analysis is performed on a direct numerical simulation dataset with non-homogeneous boundary conditions, heated on the upper side, representative of solar receivers (Antoranz et al, 2015, Int. J. Heat Fluid Flow, 55). Three flow conditions are analyzed: with friction Reynolds number equal to 180 and Prandtl number equal to 0.7 and 4 and with friction Reynolds number equal to 360 and Prandtl number equal to 0.7. Both POD and extended POD modes are presented and compared. This allows to visualize the main flow modes in terms of both turbulent kinetic energy and temperature fluctuations, analyzing their contribution to the turbulent transport of heat. The POD analysis shows that the temperature fluctuations are described by a more compact modal subspace than the turbulent kinetic energy. The effect of increasing the Reynolds number is to produce a thinner boundary layer, with a slightly less compact representation of both kinetic energy and temperature fluctuations. The increase of the Prandtl number, instead, results in a thinner thermal boundary layer with a greater scale separation between thermal fluctuations and kinetic energy. Temperature POD modes together with velocity extended POD modes are used to analyze and quantify the mode contribution to turbulent thermal transport. Results show that the correlation between velocity and temperature is such that it is possible to describe roughly 100% of the turbulent heat transport and temperature fluctuations with only 40% of the kinetic energy. For the cases with P r = 0.7, the first extended POD mode is a large vertical jet flanked by a pair of counter-rotating vortices near the heated part of the pipe. This single structure accounts for up to 10% of the turbulent heat transport.

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Quantitative measurement of spatio-temporal heat transfer to a turbulent water pipe flow

Cited by 10 publications

References 17 publications

Analysis of wall mass transfer in turbulent pipe flow combining extended proper orthogonal decomposition and Fukagata-Iwamoto-Kasagi identity

Analysis of wall mass transfer in turbulent pipe flow combining extended proper orthogonal decomposition and Fukagata-Iwamoto-Kasagi identity

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

Extended proper orthogonal decomposition of non-homogeneous thermal fields in a turbulent pipe flow

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