Numerical analysis of heat transfer and friction factor in two-pass channels with variable rib shapes

Numerical analysis of heat transfer and friction factor in two-pass channels with variable rib shapes

Arjumand RasoolAdnan Qayoum 

Mechanical Engineering Department, National Institute of Technology Srinagar, J & K, India

Corresponding Author Email: 
arjumand.beigh@yahoo.co.in
Page: 
40-48
|
DOI: 
https://doi.org/10.18280/ijht.360106
Received: 
17 August 2017
| |
Accepted: 
12 January 2018
| | Citation

OPEN ACCESS

Abstract: 

Present investigation deals with the analysis of heat transfer and friction factor for turbulent flow of air through a two-pass square channel, having ribs of various cross-sections. The cases undertaken are numerically investigated by commercial software ‘Comsol 5.2a’ using Standard k-ε model. The emphasis is towards investigating the potential impact of differing the shape of ribs for a comparative roughness pitch (p/e) of 10. Four different test cases were analyzed: square, boot, trapezoidal and house rib designs for the Reynold’s number range of 5000-52000. The Nusselt number results obtained were validated by comparing with the experimentally and computationally obtained data from earlier studies under similar conditions. The impact of the Reynold’s number on the overall performance of various rib shapes has been also investigated. The increment in average Nusselt number over that of the conventional square rib roughened channel is 1.19 and friction factor gets lowered by a factor of 1.3 as compared to square ribs respectively. The analysis shows that characteristics of heat transfer distribution and fluid flow in between the ribs are significantly influenced due to rib design and the boot-shaped rib design shows better heat transfer and friction factor performance than conventional square ribs, and therefore guarantees an enhanced thermo-hydraulic performance.

Keywords: 

local heat transfer coefficient, numerical simulation, ribs, turbine blade internal cooling

1. Introduction
2. Computational Details
3. Grid Independence Study
4. Data Reduction
5. Computational Results
6. Conclusions
Nomenclature
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