Skip to main navigation Skip to search Skip to main content

An anisotropic turbulence model for predicting heat transfer in a rotating channel

  • Chuanjie Zhang
  • , Yong Niu*
  • , Jinglei Xu
  • *Corresponding author for this work
  • Shandong Agricultural University

Research output: Contribution to journal › Article › peer-review

Abstract

This paper proposes a turbulence model correction method and an anisotropic k−ω model for predicting heat-transfer characteristics in a rotating state. We consider Reynolds numbers ranging from 3000 to 15,000, rotation numbers ranging from 0 to 1.31, and temperature ratios of 0.1, 0.17, and 0.22. Rotation corrections are made to the Reynolds stresses. Furthermore, the Reynolds stress ratio is expressed as a function of the turbulent kinetic energy Reynolds number and the rotation number to reflect the effects of the turbulent fluctuation on the Reynolds stress. Compared to the standard k−ω model, the calculation results of the anisotropic k−ω model, especially for the heat-transfer prediction at the trailing edge, are considerably improved, and in close agreement with the experimental data. The heat-transfer law at the leading edge gives a critical rotation number, which is inversely proportional to the value of the dimensionless position. By studying the buoyancy number on heat transfer, we demonstrate an increase in the rotating-to-stationary Nusselt number ratios at the trailing edge and a decrease at the leading edge, which are not obvious for buoyancy numbers less than 0.1. However, when the value is greater than 0.1, they start to increase, especially for the trailing edge.

Original languageEnglish
Article number106119
JournalInternational Journal of Thermal Sciences
Volume148
DOIs
StatePublished - Feb 2020

Keywords

  • Anisotropy
  • Critical rotation number
  • Heat transfer
  • k-ω model
  • Rotation

Fingerprint

Dive into the research topics of 'An anisotropic turbulence model for predicting heat transfer in a rotating channel'. Together they form a unique fingerprint.

Cite this