A RANS model for heat transfer reduction in viscoelastic turbulent flow

被引:20
|
作者
Masoudian, M. [1 ]
Pinho, F. T. [1 ]
Kim, K. [2 ]
Sureshkumar, R. [3 ,4 ]
机构
[1] Univ Porto, Fac Engn, Transport Phenomena Res Ctr, Rua Dr Roberto Frias S-N, P-4200465 Oporto, Portugal
[2] Hanbat Natl Univ, Dept Mech Engn, 125 Dongseo Daero, Daejeon 305701, South Korea
[3] Syracuse Univ, Dept Biomed & Chem Engn, Syracuse, NY 13244 USA
[4] Syracuse Univ, Dept Phys, Syracuse, NY 13244 USA
基金
新加坡国家研究基金会;
关键词
Newtonian and viscoelastic DNS; Drag reduction; FENE-P fluid; Viscoelastic RANS model; Heat transfer reduction; MAXIMUM DRAG REDUCTION; CHANNEL FLOW; ADDITIVES; MECHANISMS; POLYMERS; NUMBER; FLUIDS; DNS;
D O I
10.1016/j.ijheatmasstransfer.2016.04.053
中图分类号
O414.1 [热力学];
学科分类号
摘要
Direct numerical simulations (DNS) were carried out to investigate turbulent heat transfer in a channel flow of homogenous polymer solutions described by the Finitely Extensible Nonlinear Elastic-Peterlin (FENE-P) constitutive model at intermediate and high Prandtl numbers (Pr = 1.25 and 5). Time averaged statistics of temperature fluctuations, turbulent heat fluxes, thermal turbulent diffusivity, and of budget terms of the temperature variance are reported and compared with those of the Newtonian fluid cases at the same Prandtl and Reynolds numbers. Moreover, twenty one sets of DNS data of fluid flow are utilized to improve existing k-epsilon-(nu(2)) over bar -f models for FENE-P fluids to deal with turbulent flow of dilute polymer solutions up to the high drag reduction regime; specifically the dependency of closures on the wall friction velocity is removed. Furthermore, five sets of recent DNS data of fluid flow and heat transfer of FENE-P fluids were used to develop the first RANS model capable of predicting the heat transfer rates in viscoelastic turbulent flows. In this model, an existing closure for calculating the turbulent Prandtl number for Newtonian fluids is extended to deal with heat transfer in turbulent viscoelastic fluids. Predicted polymer stresses, velocity profiles, mean temperature profiles, and turbulent flow characteristics are all in good agreement with the DNS data, and show improvement over previous RANS models. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:332 / 346
页数:15
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