The multi-objective optimisation design of outlet guide vanes of diagonal flow fan based on sobol sensitivity analysis

Zijian Mao, Yu Luo, Shuiqing Zhou, Weiya Jin, Weiping Feng
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Abstract

Diagonal flow fans offer substantial energy-saving potential and find broad application across various sectors. Their performance relies heavily on factors like outlet guide vanes and spacing relative to moving blades. However, research into enhancing fan performance through optimized guide vanes and spacing remains limited. In this study, we focus on improving the accuracy of predicting the internal flow field of diagonal flow fans. This paper incorporate rotation and curvature effects using the Large Eddy Simulation (LES) model and introduce stress terms with helicity constraints to create a non-linear subgrid-scale model. This refined model enables more precise numerical simulations. By employing accurate simulations, we optimize the outlet guide vane configuration and conduct sensitivity analysis. We utilize a Radial Basis Function (RBF) model coupled with the Sobol method for this purpose. The optimized guide vane design exhibits enhanced resistance to airflow separation compared to the original, resulting in notable reductions in flow losses within the grille channel. Experimental tests are performed on the diagonal flow fan both before and after optimization. At the specified operating point, the second guide vane optimization leads to a 1.28 m 3 /min increase in fan flow, a 4.33% rise in total pressure efficiency, and a 2.2 dB noise reduction. These findings underscore the accuracy of the helicity correction model in predicting diagonal flow fan behavior. The multi-objective optimization approach, combining the RBF proxy model with the Sobol method, proves highly reliable. It offers valuable design insights for similar fans and establishes a credible design methodology.
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基于sobol敏感性分析的斜流风机出口导叶多目标优化设计
斜流风机提供了大量的节能潜力,并在各个部门找到广泛的应用。它们的性能在很大程度上依赖于出口导叶和相对于动叶的间距等因素。然而,通过优化导叶和间距来提高风扇性能的研究仍然有限。在本研究中,我们着重于提高对角流风机内部流场的预测精度。本文采用大涡模拟(LES)模型,结合旋转和曲率效应,并引入带有螺旋约束的应力项,建立非线性亚网格尺度模型。这个改进的模型使数值模拟更加精确。通过精确的仿真,优化了出口导叶结构,并进行了灵敏度分析。为此,我们利用径向基函数(RBF)模型与Sobol方法相结合。优化后的导叶设计与原来的设计相比,对气流分离的阻力增强,从而显著减少了格栅通道内的流动损失。对优化前后的斜流式风机进行了实验测试。在指定工况点,第二导叶优化后,风机流量提高1.28 m3 /min,总压效率提高4.33%,噪声降低2.2 dB。这些发现强调了螺旋度校正模型在预测斜流风机行为方面的准确性。将RBF代理模型与Sobol方法相结合的多目标优化方法具有较高的可靠性。它为类似的粉丝提供了有价值的设计见解,并建立了可靠的设计方法。
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来源期刊
CiteScore
3.30
自引率
5.90%
发文量
114
审稿时长
5.4 months
期刊介绍: The Journal of Power and Energy, Part A of the Proceedings of the Institution of Mechanical Engineers, is dedicated to publishing peer-reviewed papers of high scientific quality on all aspects of the technology of energy conversion systems.
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