Study of Conjugate Heat Transfer from a Flat Plate by Turbulent Offset Jet Flow

Vishnuvardhanarao, E.; Das, Manab Kumar

doi:10.1080/10407780701678331

Cited by 13 publications

(4 citation statements)

References 21 publications

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“…Based on the comparison with experimental results, it has been found that LRN turbulence model proposed by Yang and Shih (1993) and k −ω SST model perform better. Vishnuvardhanarao and Das (2007) have reported the conjugated heat transfer from a solid slab subjected to constant heat flux boundary condition by turbulent plane offset jet for Re = 15000. High-Reynolds-number (HRN) standard k − ε model in conjunction with wall functions has been applied for turbulence modeling.…”

Section:    mentioning

confidence: 99%

Study of Conjugate Heat Transfer from Heated Plate by Turbulent Offset Jet in Presence of Freestream Motion using Low-Reynolds Number Modeling

Rathore

2019

JAFM

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The present study deals with conjugate heat transfer from a heated flat plate by a turbulent offset jet in presence of freestream motion. The turbulent convection in fluid and conduction in solid is solved in a coupled manner by simultaneously satisfying the equality of temperature and heat flux at the solid-fluid interface. The computations have been carried out using low-Reynolds number (LRN) k −ω SST model in the fluid region. The capability of LRN modeling have enabled to solve the entire boundary layer including the thin viscous sublayer due to which Moffatt vortices (secondary recirculation regions) have been captured near the corner of the wall where the turbulence Reynolds number is low. The bottom surface of solid plate is maintained at a constant temperature higher than the jet inlet temperature whereas the jet inlet temperature is same as that of the ambient. The present investigation reports the effects of offset ratio of jet (OR), Reynolds number of flow (Re), solid to fluid thermal conductivity ratio (K), solid slab thickness (S) and freestream velocity (U∞) on conjugate heat transfer arises due to solid and fluid interaction. The offset ratio is varied in the range OR = 3 − 11, Reynolds number in the range Re = 10000 − 25000, solid to fluid thermal conductivity ratio in the range K = 1 − 2000, solid slab thickness in the range S = 1−20 and freestream velocity in the range U∞ = 0.1 − 0.25. The effects of various parameters on the near-wall velocity profile, solid-fluid interface temperature, local Nusselt number variation along the plate, heat flux variation along the plate, etc. have been discussed in detail.

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Section:    mentioning

confidence: 99%

Study of Conjugate Heat Transfer from Heated Plate by Turbulent Offset Jet in Presence of Freestream Motion using Low-Reynolds Number Modeling

Rathore

2019

JAFM

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“…Thus, over the years a growing interest is observed in the study of CHT by researchers. Much work has been done for CHT on a flat plate 4–18 . Chiu et al 19 carried out a numerical as well as an experimental investigation of CHT in a horizontal channel containing a heated section.…”

Section: Introductionmentioning

confidence: 99%

ψ‐v Computation of steady‐state conjugate heat transfer in backward‐facing step flow

2021

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In this paper, we study steady‐state conjugate heat transfer over a backward‐facing step flow using a combination of a compact finite difference scheme for the ψ ‐ v form of the Navier–Stokes equations and a higher‐order compact scheme for the temperature equations on nonuniform grids. We investigate the effect of Reynolds number ( 200 ≤ R e ≤ 800 ), conductivity ratio ( 1 ≤ k ≤ 1000 ), Prandtl number ( 0.1 ≤ P r ≤ 15 ), and slab thickness ( h ≤ b ≤ 6 h ) on the heat transfer characteristics. Isotherms remain clustered near the reattachment point in the fluid, while the temperature in the solid decreases vertically, with the minima at the reattachment point. Heat transfer rate (HTR) increases with Re, the maximum at the reattachment point. The HTR increases with k till k = 100 after, which it becomes invariant as k → ∞ . Isotherms at the inlet become more disorderly with increasing Pr, and progressively clustered near the interface, indicating an increase in HTR, while the temperature in the solid region decreases with Pr. Increasing b decreases the HTR. In addition to obtaining an excellent match with results previously reported in the literature, we offer more comprehensive and previously unreported insights on flow physics.

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“…Predicting the temperature field accurately is the premise in designing a high-performance cooling system. With the rapid development of CFD technology and computer science, three-dimensional numerical simulations using the conjugate heat transfer (CHT) algorithm have become effective methods for accurately predicting the temperature field of turbine blades and other hot-end components [3][4][5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%