A Kinetic Perspective on k‒ε Turbulence Model and Corresponding Entropy Production

Asinari, Pietro; Fasano, Matteo; Chiavazzo, Eliodoro

doi:10.3390/e18040121

Cited by 11 publications

(16 citation statements)

References 75 publications

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“…In any point of a convective field, irreversibilities are produced by two distinct mechanisms: heat flow and friction. Bejan [8], Adeyinka and Naterer [3] and Asinari et al [5] give comprehensive reviews of the theory. A brief summary is presented here.…”

Section: Entropy Generation In Fluid Flowmentioning

confidence: 99%

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

et al. 2018

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In recent years, a number of authors have studied entropy generation in Wells turbines. This is potentially a very interesting topic, as it can provide important insights into the irreversibilities of the system, as well as a methodology for identifying, and possibly minimizing, the main sources of loss. Unfortunately, the approach used in these studies contains some crude simplifications that lead to a severe underestimation of entropy generation and, more importantly, to misleading conclusions. This paper contains a re-examination of the mechanisms for entropy generation in fluid flow, with a particular emphasis on RANS equations. An appropriate methodology for estimating entropy generation in isolated airfoils and Wells turbines is presented. Results are verified for different flow conditions, and a comparison with theoretical values is presented. 1Wells turbines have been studied extensively, both experimentally [15,31,24,63,74,53,57,48] and numerically [40,62,17,76,30,72,32,27], but mainly from a first-law perspective. More recently, a number of authors [66,67,68,69,71] have focused on the irreversibilities in this component, trying to link the amount of available work (exergy) and the entropy produced.The application of second-law analyses is not novel, as such analyses have been done by many authors, but mainly from a system perspective: Bejan [8,9] presents an extensive review of the application to different thermodynamic systems. Similar approaches have been used in the analysis of thermal power plants [39], wind turbines [56,6,7,60,52], and vortex generators [33].Computational Fluid Dynamics (CFD), aside from making possible a more rapid and economic evaluation of many systems (compared to experimental testing), can provide a better and more detailed understanding of many phenomena, by capturing a level of detail that would be extremely difficult in an experimental study. It allows a very fine decomposition of the overall problem that can be used to locate the sources of irreversibility within the system. Entropy generation by thermal and viscous sources can be calculated directly by post-processing the fields of thermo-and fluid-dynamic variables available from the numerical solution [8]. However, particular attention needs to be paid to the nature of the flow and to the solution approach. While in laminar flows all entropy generation is directly found in the CFD solution [18,2,70,33,79,59], this is not true for turbulent flows, unless a Direct Numerical Simulation (or DNS) is used. However, with current computational resources, the use of DNS is still impractical even for moderately large Reynolds numbers. To make high-Reynolds-number flows treatable, the governing equations are either averaged (leading to the Reynolds Averaged Navier Stokes equations, or RANS) or filtered (leading to the Large Eddy Simulation approach, or LES).Moore and Moore [49, 50] present a methodology for calculating entropy production in viscous flows, using RANS equations. They divide the mean entropy production into the contr...

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Section: Entropy Generation In Fluid Flowmentioning

confidence: 99%

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

et al. 2018

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“…where λ p is expected to strongly influence the convective heat transfer mechanism: low values should lead to enhanced heat transfer due to perturbation of the boundary layer, whereas high values should cause stagnation phenomena, thus inducing a reduction in the convection [48]. The other parameters are defined similarly to what was previously discussed regarding the ESR patterns.…”

Section: Cones Patternsmentioning

confidence: 99%

Convective Heat Transfer Enhancement through Laser-Etched Heat Sinks: Elliptic Scale-Roughened and Cones Patterns

et al. 2020

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The efficient dissipation of localized heat flux by convection is a key request in several engineering applications, especially electronic ones. The recent advancements in manufacturing processes are unlocking the design and industrialization of heat exchangers with unprecedented geometric characteristics and, thus, performance. In this work, laser etching manufacturing technique is employed to develop metal surfaces with designed microstructured surface patterns. Such precise control of the solid-air interface (artificial roughness) allows to manufacture metal heat sinks with enhanced thermal transmittance with respect to traditional flat surfaces. Here, the thermal performance of these laser-etched devices is experimentally assessed by means of a wind tunnel in a fully turbulent regime. At the highest Reynolds number tested in the experiments ( R e L ≈ 16 , 500 ), elliptic scale-roughened surfaces show thermal transmittances improved by up to 81% with respect to heat sinks with flat surface. At similar testing conditions, cones patterns provide an enhancement in Nusselt number and thermal transmittance of up to 102% and 357%, respectively. The latter results are correlated with the main geometric and thermal fluid dynamics descriptors of the convective heat transfer process in order to achieve a predictive model of their performance. The experimental evidence shown in this work may encourage and guide a broader use of micro-patterned surfaces for enhancing convective heat transfer in heat exchangers.

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“…In classical turbulence it is assumed that the extra turbulent contribution to the evolution equation for v, namely the third term of equation (2.7), has a form analogous to that of the usual viscous term, but with an effective viscosity of turbulent origin. Thus, it is taken [9,10,11,14]…”

Section: A Short Remainder Of the K − Modelmentioning

confidence: 99%

“…Here we are interested in the K − model as the zero-th order closure model in the hierarchy of the moments of the fluctuations of the main fields, usually applied in a viscous classical fluid [14]. In this paper we aim at generalizing this method to superfluid helium, where an additional different kind of turbulence occurs: quantum turbulence.…”

Section: Introductionmentioning

confidence: 99%

“…In the context of the present paper, we analize the equations, identify the turbulent contributions, propose for them some turbulent transport coefficients, and try to express them in terms of the second moments v, q and L, namely K, K q and K L , as well as of their corresponding dissipation functions , q and L , related to the second-order moments of their gradients. Since some of the details may depend on the kind of flow, we do not pretend that this model will grasp all the complexity of turbulence, but it is logical to take it into consideration as a macroscopic starting point, in analogy to the K − model in classical turbulence [1,4,8,9,10,11,14].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

K-ϵ-L model in turbulent superfluid helium

Sciacca

Jou

Mongiovı̀

2020

Physica A: Statistical Mechanics and its Applications

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A Kinetic Perspective on k‒ε Turbulence Model and Corresponding Entropy Production

Cited by 11 publications

References 75 publications

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

Convective Heat Transfer Enhancement through Laser-Etched Heat Sinks: Elliptic Scale-Roughened and Cones Patterns

K-ϵ-L model in turbulent superfluid helium

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