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    基于改进Kriging代理模型的自适应序列优化算法在离心压缩机蜗壳设计中的应用

    Application of Adaptive Sequential Optimization Algorithm Based on Kriging Surrogate Model in Design of Centrifugal Compressor Volute

    • 摘要: 提出了一种基于改进Kriging代理模型的自适应序列优化算法,并利用Matlab软件开发相应的优化平台.采用该优化平台,针对某特定流量工况,以质量流量平均总压损失系数为目标变量对离心压缩机蜗壳系统模型进行气动优化设计,并对优化前后蜗壳模型进行对比计算,来验证优化结果在实际蜗壳系统中的适用性.结果表明:优化后蜗壳的总压损失系数小、静压恢复系数大,性能得到改善.

       

      Abstract: An adaptive sequential optimization algorithm was presented based on improved Kriging surrogate model, while a corresponding optimization platform was developed using Matlab software, with which an aerodynamic optimization design was carried out for a centrifugal compressor volute by taking the total pressure loss coefficient as the target variable. A comparative calculation was made for the compressor volute before and after optimization, so as to verify the applicability of the platform in design of actual compressor volutes. Results show that after optimization, the total pressure loss coefficient is decreased and the static recovery coefficient is increased, resulting in improved performance of the compressor volute.

       

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