基于多目标遗传算法的流体力学仿真计算辅助教学系统设计  

Design of computing auxiliary teaching system for fluid mechanics simulation based on multi-target genetic algorithm

作　　者：李敏[1] 孙佳秋 LI Min;SUN Jiaqiu(Tianjin College,University of Science and Technology Beijing,Tianjin 301830,China)

机构地区：[1]北京科技大学天津学院,天津301830

出　　处：《无线互联科技》2024年第23期44-46,共3页Wireless Internet Science and Technology

基　　金：天津市市级一流课程-流体力学A,项目编号:YLKC202101-津教高函〔2024〕12号。

摘　　要：为满足复杂流体力学问题的多目标优化需求,优化辅助教学效果,文章利用多目标遗传算法,设计了一种更高准确性、更强针对性流体力学仿真计算辅助教学系统。首先,对计算服务器、存储设备、显示设备以及输入输出设备进行选型设计,为系统运行提供硬件支持。其次,设计流体力学仿真计算数据库,分类存储与流体力学仿真计算相关的数据。最后,在此基础上,利用多目标遗传算法进行流体力学仿真计算,以输出满足多个约束条件的最优解。测试结果表明,该系统应用后,在仿真计算资源辅助分配的正确性上始终保持着显著的优势,适用于实际流体力学仿真计算的辅助教学。In order to meet the multi-objective optimization requirements of complex fluid mechanics problems and optimize the effectiveness of auxiliary teaching,this article designs a higher accuracy and stronger targeted fluid mechanics simulation calculation auxiliary teaching system using multi-objective genetic algorithm.Firstly,select and design computing servers,storage devices,display devices,and input/output devices to provide hardware support for system operation.Secondly,design a fluid dynamics simulation calculation database to classify and store data related to fluid dynamics simulation calculations.Finally,based on this,multi-objective genetic algorithm is used for fluid dynamics simulation calculation to output the optimal solution that satisfies multiple constraint conditions.The test results show that the system maintains significant advantages in the accuracy of simulation computing resource allocation after application,and is suitable for assisting teaching in practical fluid mechanics simulation calculations.

关 键 词：多目标遗传算法 流体力学 仿真 计算 辅助教学系统 

分 类 号：G642[文化科学—高等教育学]