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最优预测元模型在小型离心式鼓风机性能优化中的应用

李科钦 周忠宁 李意民 纪子宁 周志恒 包昊森

流体机械2025,Vol.53Issue(1):105-112,8.
流体机械2025,Vol.53Issue(1):105-112,8.DOI:10.3969/j.issn.1005-0329.2025.01.013

最优预测元模型在小型离心式鼓风机性能优化中的应用

Application of metamodel of optimal prognosis in performance optimization of small centrifugal blowers

李科钦 1周忠宁 1李意民 1纪子宁 1周志恒 1包昊森1

作者信息

  • 1. 中国矿业大学 低碳能源与动力工程学院,江苏 徐州 221116
  • 折叠

摘要

Abstract

Addressing the issues inherent in traditional aerodynamic design methods for blades—such as reliance on designer experience,long development cycles,and difficulty in ensuring design precision—this study applies an optimal surrogate model optimization method to the impeller optimization of a centrifugal blower.By parameterizing the design of a small centrifugal blower and using the Advanced Latin Hypercube Sampling(ALHS)method to sample 36 parameters from the meridional profile,inlet and outlet blade angles,and blade surface twist angle,200 sets of blower performance data were constructed through numerical simulations.Based on this data,the optimal surrogate model(MOP)was employed to identify the 9 parameters that most significantly impact blower performance.Subsequently,an evolutionary algorithm(EA)was utilized to iteratively compute the optimal values of these 9 parameters,with the objective of maximizing isentropic efficiency and constraining the inlet-outlet pressure difference.A comparative analysis of the flow fields before and after optimization was conducted.The results demonstrate that the optimized blower suppressed tip leakage flow,reducing the tip leakage flow rate by 10%compared to the original model.At the mid-span of the impeller(at 55%of the meridional streamline),the maximum fluid velocity along the blade height decreased from 101.66 m/s to 82.06 m/s after optimization,and the velocity variation ∆V reduced from 53.52 m/s to 40.74 m/s,indicating reduced flow losses.Additionally,the maximum pressure at the impeller outlet increased from 115.37 kPa to 116.19 kPa.The optimal surrogate model effectively filters out non-critical input parameters during the optimization process,thereby reducing optimization costs and time.The findings of this research provide a reference for the optimal design of centrifugal blowers.

关键词

小型离心式鼓风机/参数优化/最优预测元模型/数值模拟

Key words

small centrifugal blower/parameter optimization/metamodel of optimal prognosis/numerical simulation

分类

机械制造

引用本文复制引用

李科钦,周忠宁,李意民,纪子宁,周志恒,包昊森..最优预测元模型在小型离心式鼓风机性能优化中的应用[J].流体机械,2025,53(1):105-112,8.

基金项目

国家自然科学基金项目(51776217) (51776217)

流体机械

OA北大核心

1005-0329

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