拉丁超立方体抽样
数学优化
数学
参数统计
多目标优化
混合器
优化设计
遗传算法
混合(物理)
应用数学
替代模型
计算机科学
物理
蒙特卡罗方法
量子力学
统计
作者
Arshad Afzal,Kwang‐Yong Kim
标识
DOI:10.1080/00986445.2013.841150
摘要
This paper presents a multi-objective optimization procedure for the design of a sigma micromixer. The procedure combines three-dimensional analyses of fluid flow and mixing, polynomial approximation of objective functions, and a multi-objective genetic algorithm (MOGA). MATLAB Optimization Toolbox (version 7.7, The Mathworks, Inc., MA, USA) was used to invoke MOGA for optimization. A brief discussion on the application of Toolbox is introduced in the paper. Three geometric design parameters concerning the shape of the sidewalls were exploited for optimization. Mixing index and non-dimensional pressure loss were selected as objective functions. For mixing analysis, steady Navier-Stokes equations with a convection-diffusion model for scalar transport were solved at the Reynolds number Re = 0.91. The design space was explored through parametric study, and the Latin hypercube sampling method was used as a design-of-experiment technique for selection of the design points in the design space. Surrogate modeling was performed for the objective functions using response surface approximation. Pareto-optimal solutions in the functional space lying on the Pareto-optimal curve were obtained.
科研通智能强力驱动
Strongly Powered by AbleSci AI