Abstract

By setting two vortex tubes in hot cascade type Vortex tube manner, can achieve two cooling points for spot cooling applications with the single input. These cooling points play a vital role to cool tools in machining operations. The present work aims to optimize the output parameters such as outlet temperature, Coefficient of Performance (COP). Based on the literature, the performance of this vortex tube mainly depends on its input parameters such as air inlet pressure, length to diameter ratio, and the number of nozzles. In the present work, the above input parameters have been experimented on this vortex tube, based on the Taguchi L18 array. The optimal condition for both temperatures, COP at hot and cold outlets was calculated using grey relational analysis (GRA). The obtained experimental results were analyzed using the ANOVA approach. Also for multi responses, 1st and 2nd order predicted mathematical models developed by using Minitab 18 software and its accuracy checked. The achieved results are at first spot cooling point temperature 294.9 K, COPc1 as 0.0203, second spot cooling point temperature 284.2 K, and COPc2 as 0.1628. This work proved that for solving multi-attribute decision-making problems, grey relational analysis methodology was efficient.

Highlights

  • The pressurized gas/air as an input for the vortex tube and this was split into two streams; one is towards the cold outlet and another one as a hot outlet

  • By using Response Surface Methodology (RSM), Prabakaran et al [6] have proved that the diameter of the nozzle, inlet air pressure are the most influencing factors for the cold end side temperature difference and performance of the vortex tube

  • In this experimental investigation the input parameters were taken as inlet pressure of air, length (L)/diameter (D) ratio, nozzles number to optimize the temperature and coefficient of performance (COP) at hot outlets and cold outlets through grey relational analysis

Read more

Summary

Introduction

The pressurized gas/air as an input for the vortex tube and this was split into two streams; one is towards the cold outlet and another one as a hot outlet. Pinar et al [3], succeeded to improve the temperature difference between hot, cold ends of the Vortex Tubes and statistically proved that the air pressure at the inlet, L/D ratio, and nozzles are significant factors in this study. By using Response Surface Methodology (RSM), Prabakaran et al [6] have proved that the diameter of the nozzle, inlet air pressure are the most influencing factors for the cold end side temperature difference and performance of the vortex tube. In this experimental investigation the input parameters were taken as inlet pressure of air, length (L)/diameter (D) ratio, nozzles number to optimize the temperature and coefficient of performance (COP) at hot outlets and cold outlets through grey relational analysis.

Grey relational analysis optimization methodology
Experimental details
Implementation of grey relational analysis
Results and discussion gi 1 n
Second order model
Conclusions

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.