Optimization of Convective Heat Transfer Model of Cold Storage with Rectangular Pin Finned Evaporator Using Taguchi Regression, S/N Ratio and ANOVA Analysis

Optimization of Convective Heat Transfer Model of Cold Storage with Rectangular Pin Finned Evaporator Using Taguchi Regression, S/N Ratio and ANOVA Analysis

N. Mukhopadhyay Tapan Mondal

Assistant Professor, Department of Mechanical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri-735102, West Bengal, India

Post Graduate scholar, Department of Mechanical Engineering, Jalpaiguri Government Engineering College, Jalpaiguri-735102, West Bengal, India

Corresponding Author Email: 
nm1231@gmail.com; nm_1231@rediffmail.com; tapanmondal876@gmail.com
Page: 
830-849
|
DOI: 
https://doi.org/10.18280/mmc_b.860402
Received: 
18 September 2017
|
Accepted: 
15 October 2017
|
Published: 
31 December 2017
| Citation

OPEN ACCESS

Abstract: 

This work contains of design of experiments to optimize the various control factors of a cold storage evaporator space inside the cold room, in other words the heat absorption by evaporator will be maximize to minimize the use of electrical energy to run the system. Here we have use rectangular pin fin to maximize the heat absorption by evaporator. Taguchi orthogonal array with regression analysis have been used as a design of experiments. The control factors are Area of the evaporator with rectangular pin fin(A), temperature difference of the evaporator space (dT), and relative humidity inside the cold room(RH). The Taguchi S/N ratio analysis have used as an optimization technique. Larger the better type S/N ratio have used for calculating the optimum level of control parameters, because it is a maximization problem. Analysis of variance ANOVA was also performed on the test results to find out the significant control factors.

Keywords: 

Taguchi orthogonal array, Convective heat transfer co-efficient, Rectangular pin fin area and arrangement, Regression analysis, Graphical representation of control factors with heat transfer, S/N ratio analysis, ANOVA analysis.

1. Introduction
2. Model Development
3. Results and Discussions
Conclusion
  References

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