克里金
消散
参数统计
叶轮
静压
转化(遗传学)
离心风机
计算流体力学
流量(数学)
机械
结构工程
数学
计算机科学
几何学
工程类
机械工程
物理
统计
入口
基因
热力学
生物化学
化学
作者
Meijun Zhu,Zhehong Li,Guohui Li,Xinxue Ye,Yang Liu,Ziyun Chen,Ning Li
出处
期刊:Processes
[Multidisciplinary Digital Publishing Institute]
日期:2023-06-08
卷期号:11 (6): 1751-1751
被引量:2
摘要
Class and shape transformation functions are proposed to carry out the parametric design of the blade profiles because fan efficiency is closely related to the shape of blade profiles. An optimization with the objectives of fan efficiency and static pressure based on the Kriging models was established, and numerical simulation data were applied to construct the Kriging models. The dissipation function was used to analyze the fan energy loss. The prediction results show that the maximum accuracy error between the Kriging model and the experimental data is approximately 0.81%. Compared with the prototype fan, the optimized fan was able to ameliorate the distribution of the flow field pressure and velocity; the outlet static pressure increased by 9.03%, and the efficiency increased by 2.35%. The dissipation function is advantageous because it can intuitively indicate the location and amount of energy loss in the fan, while effectively obtaining the total energy loss as well. The situation of energy loss was mutually validated with the density of the static pressure contours and the streamline distribution. The flow fields at the leading edge of the optimized fans were improved by analysis of the dissipation function, and the leading edges of the three impellers selected from the Pareto front were narrower and flatter than those of the prototype fan.
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