叶轮
拉丁超立方体抽样
替代模型
稳健性(进化)
气体压缩机
计算流体力学
离心式压缩机
解算器
灵敏度(控制系统)
稳健优化
涡轮增压器
涡轮机械
实验设计
计算机科学
机械工程
蒙特卡罗方法
工程类
数学优化
数学
机器学习
统计
航空航天工程
基因
化学
生物化学
程序设计语言
电子工程
作者
Adeel Javed,René Pecnik,Jos P. van Buijtenen
摘要
Compressor impellers for mass-market turbochargers are die-casted and machined with an aim to achieve high dimensional accuracy and acquire specific performance. However, manufacturing uncertainties result in dimensional deviations causing incompatible operational performance and assembly errors. Process capability limitations of the manufacturer can cause an increase in part rejections, resulting in high production cost. This paper presents a study on a centrifugal impeller with focus on the conceptual design phase to obtain a turbomachine that is robust to manufacturing uncertainties. The impeller has been parameterized and evaluated using a commercial computational fluid dynamics (CFDs) solver. Considering the computational cost of CFD, a surrogate model has been prepared for the impeller by response surface methodology (RSM) using space-filling Latin hypercube designs. A sensitivity analysis has been performed initially to identify the critical geometric parameters which influence the performance mainly. Sensitivity analysis is followed by the uncertainty propagation and quantification using the surrogate model based Monte Carlo simulation. Finally, a robust design optimization has been carried out using a stochastic optimization algorithm leading to a robust impeller design for which the performance is relatively insensitive to variability in geometry without reducing the sources of inherent variation, i.e., the manufacturing noise.
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