摘要
为研究医用涡轮各参数对涡轮性能的影响,文中采用Isight集成CFturbo和pumplinx研发平台,快速实现从气动设计到数值模拟以及优化设计的全部过程。针对一款医用呼吸机涡轮进行初步气动设计,设计完成后以叶轮参数D2、Ds、B2、Z、β1、β2、θ作为设计变量,涡轮的压升ΔP和气动效率η最高为目标进行自动数值优化。其中试验样本由最优拉丁超立方方法确定。目标函数的权重因子由超传递近似法确定。采用此方法优化设计后,涡轮压升由原来2584 Pa增加至3339 Pa,压升增加29.2%。效率η由90.06%增加至95.64%,效率增加5.8%。
This paper applies genetic algorithm to study the influence of various parameters on performance of medical turbine.Isight integrated CFturbo and Pumplinx development platform are used to quickly realize the whole process from aerodynamic design to numerical simulation and optimization design.A preliminary aerodynamic design is carried out for a medical ventilator turbine.After the design is completed,the impeller parameters D2,Ds,B2,Z,β1,β2 andθare taken as the design variables,and the turbine pressure riseΔP and aerodynamic efficiencyηare optimized automatically.The experimental samples are determined by the optimal Latin hypercube method.The weight factor of objective function is determined by hypertransfer approximation.The turbine pressure rise increases from 2584 Pa to 3339 Pa,increases by 29.2%after optimized design.The efficiencyηincreases from 90.06%to 95.64%,and the efficiency increases by 5.8%.
作者
郝开元
黄宁
HAO Kaiyuan;HUANG Ning(Beijing Aerospace Propulsion Institute,Beijing 100076,China)
出处
《机械工程师》
2023年第5期82-84,共3页
Mechanical Engineer
关键词
医用涡轮
优化设计
遗传算法
CFD
medical turbine
optimization design
genetic algorithm
CFD
