Genetic Algorithm based Finite Difference Simulation of Solidification Process for MMC's. (2018)

• Record Type: Journal Article
• Authors: Kosti, Siddhartha; Pathak, Priya
• Is Part Of: Materials today. Volume 5:Number 2(2018)Part 2
• Page Start: 8271
• Page End: 8279
• Publication Date: 2018
• Subjects: Genetic algorithm -- Solidification -- Finite Difference modelling -- MMCs -- Time-temperature curve; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2017.11.518
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: During solidification process, thermal conductivity plays the vital role. In our work, we apply the genetic algorithm to find out best material for our product. First we choose base material in selection procedure of genetic and all remained material treated as chromosomes, crossover happen between base material and chromosome, fitness of the generated offspring (MMCs – Metal Matrix Composites) checked by thermal value, after that in tournament selection parent is replaced by new most fitted offspring, this process call iteratively until or unless we find better offspring for our product. For fitted offspring, unsteady heat conduction equation in 3D form is solved. Two thermal conductivity models (Mixture rule and Maxwell model) are considered. Experimental validation of the present results is also performed. Time-temperature history curve is plotted for the best-fitted offspring. At the end, time-temperature history curve is also plotted for other generated offspring to compare the results. Result reveals that with the addition of reinforcement chromosome time-temperature history curve becomes steeper. The increment in wt.% of reinforced chromosome also makes the time-temperature curve steeper indicating increment in solidification rate. Both the thermal conductivity models give almost same time-temperature history curve.