jaya algorithm

In this study, the design of a nanofluid driven shell and tube heat exchanger is optimized, for the first time, by use of three multi objective algorithms. Two different operating conditions are investigated to compare the performance of the algorithms based on an economic model (cost function). Based on the obtained results, the Genetic, Particle Swarm and Jaya optimization algorithms can all improve the design. The amount of design improvement by each method is 9.66%, 10.63% and 10.9% respectively. Also from the view point of optimization time, Jaya optimization algorithm has relatively less CPU time than the other two algorithms, which in fact, reduces computational costs in complicated computations. Finally, due to the good performance of Jaya optimization algorithm in comparison with other considered algorithms, the performance of the heat exchangers is evaluated for using Ag, TiO2 and Al2O3 nanofluids of 0.5% to 5 vol.% by this algorithm. A performance evaluation factor (PE) is introduced as the criterion for simultaneous investigation of thermal and hydraulic performance of nanofluids. The results show that silver nanofluid, among other ones has better performance.

In order to minimise the difficulties associated in selecting conventional coolants in any machining, cutting fluids like vegetable based oils can serve as a viable alternative. Vegetable based oils when used in combination with eco-friendly techniques like MQL/NDM can have a major impact in any machining. In the present paper, performance characteristics of surface roughness and tool wear in machining of EN 36 steel alloy under Near Dry machining conditions/ Minimum quantity lubrication using vegetable based oil lubricant is studied. The input parameters like MQL flow rate, speed, feed and depth of cut for 5 levels are used in the CCD approach of Response surface methodology. For improving the machinability of alloy steel and to predit the values a regression equation is designed and developed between the input parameter and the output parameters. A multi-response optimum model for the output responses was also developed using RSM, GRA and JAYA algorithm, It was observed from the experiment results that JAYA algorithm has been proved the best multi-response optimization technique when compared to grey relational analysis and RSM.