Abstract

Attending to the recent developments of computer hardware and software technologies now is a suitable time for utilizing the smart optimizer algorithms for shape designing in different engineering problems. In this study, a combination of a modified parallel genetic algorithm, image processing and computational fluid dynamics has been presented for obtaining optimum shapes for different multi-objective targets. For this purpose, a homemade MATLAB code is developed to find the optimized solid structures considering different transport phenomena targets, such as heat transfer rate, pressure drop, mass transfer rate, aerodynamic property, etc. The main purpose of this study is to develop a modified parallel genetic algorithm for numerical solving of high calculation cost optimizations in the fluid mechanic fields. The presented approach in this study starts a novel parallel calculation method for the optimization of different parameters in the fluid flow fields using the heavy numerical calculations of computational fluid dynamics. After the presentation of the overall view of this method, a case study is optimized for illustrating the ability of this method for utilizing a network of computer cores for parallel optimization of these high-time-consuming computational fluid dynamics-based optimizations. In this case, a certain shape optimization has been investigated for minimizing the entered drag force to it by a passing fluid flow..

Keywords:Parallel calculations; Shape optimization; Modified genetic algorithm; Image processing; Computational fluid dynamics