Multi-objective Optimization Based on Unsteady Analysis Considering the Efficiency and Radial Force of a Single-Channel Pump for Wastewater Treatment
Multi-objective Optimization Based on Unsteady Analysis Considering the Efficiency and Radial Force of a Single-Channel Pump for Wastewater Treatment作者机构：Thermal & Fluid System R&D Group Korea Institute of lndustrial Technology Cheonan Republic of Korea Advanced Energy and Technology University of Science and Technology Daejeon Republic of Korea
出 版 物：《Journal of Mechanics Engineering and Automation》 (机械工程与自动化（英文版）)
年 卷 期：2016年第6卷第5期
页 面：234-245页
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 070105[理学-运筹学与控制论] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Single-channel pump efficiency radial force sweep area unsteady analysis optimization.
摘 要：A multidisciplinary optimization was conducted to simultaneously improve the efficiency and reduce the radial force of a single-channel pump for wastewater treatment. A hybrid multi-objective evolutionary algorithm was coupled with a surrogate model to optimize the geometry of the single-channel pump volute. Steady and unsteady Reynolds-averaged Navier-Stokes equations with a shear stress transport turbulence model were discretized using finite volume approximations and were then solved on tetrahedral grids to analyze the flow in the single-channel pump. The three objective functions represented the total efficiency, the sweep area of the radial force during one revolution, and the distance of the mass center of sweep area from the origin while the two design variables were related to the cross-sectional area of the internal flow of the volute. Latin hypercube sampling was employed to generate twelve design points within the design space, and response surface approximation models were constructed as surrogate models for the objectives based on the values of the objective function at the given design points. A fast non-dominated sorting genetic algorithm for local search was coupled with the surrogate models to determine the global Pareto-optimal solutions. The trade-off between the objectives was determined and was described in terms of the Pareto-optimal solutions. The results of the multi-objective optimization showed that the optimum design simultaneously improved the efficiency and reduced the radial force relative to those of the reference design.
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