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Turbulence models performance to predict fluid mechanics and heat transfer characteristics of fluids flow in micro-scale channels

Eduardo Miranda, Daniel Felipe Sempértegui-Tapia, Cristian A. Chávez

2024Numerical Heat Transfer Part A Applications11 citationsDOI

Abstract

The predictability of the mathematical models on the details and the phenomenology for microscale flow conditions is an open topic in the literature. In this sense, this work evaluates the capacity of the following turbulence models: standard k−ε, RNG k−ε, k−ω standard, k−ω SST, Realizable k−ε, and Low-Re k−ε to predict the fluid mechanics and heat transfer characteristics of low Global Warming Potential (GWP) fluid flow in a 1.1 mm ID microchannel. These turbulence models are evaluated for Reynolds Numbers up to 104. The numerical results for velocity profile, friction factors, and Nusselt Numbers are validated with analytical and experimental data published in previous works for R134a, R1234yf, R1234ze(E), and R600a. Parametric behaviors of pressure drop and heat transfer coefficient are presented and analyzed. The results indicate that each of the models describes the qualitative behavior of flow and heat transfer processes. On the other hand, the quantitative results indicate that the Low-Re k−ε,k−ω, and k−ω SST models demonstrate an acceptable prediction of some variable’s behavior. Numerically, the Low-Re k−ε model presents an accurate prediction with the lowest mean absolute.

Topics & Concepts

TurbulenceHeat transferMechanicsFluid mechanicsFluid dynamicsScale (ratio)Flow (mathematics)Statistical physicsPhysicsQuantum mechanicsHeat Transfer and OptimizationHeat Transfer and Boiling StudiesHeat Transfer Mechanisms
Turbulence models performance to predict fluid mechanics and heat transfer characteristics of fluids flow in micro-scale channels | Litcius