Optimization design of hydrogen Laval nozzle based on response surface methodology (RSM)

Jianyang Fang, Yusheng Ju, Liwei Mao, Shichao Pei
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Abstract

To conduct an in-depth study of the injection characteristics of gas fuels, the structural parameters of the nozzle are optimized. Utilizing the Response Surface Method (RSM), this study selects an inlet radius R1, outlet radius R2, throat straight radius R0, expansion half angle θ, and contraction half angle α as design parameters. Based on the validated numerical model, a response surface prediction model for outlet velocity v and mass flow rate Q is established. Using the derived expressions, the contribution and interactive effects of design variables on response variables are analyzed. The findings indicate that the outlet radius and throat radius significantly affect the outlet velocity. The outlet radius positively correlates with the outlet velocity, while the throat radius negatively correlates with it. The mass flow rate is most significantly influenced by the throat radius, increasing with its increase. With outlet velocity and mass flow rate as optimization objectives, the MOGA algorithm is applied for multi-objective optimization. The optimization results indicate that the optimized structural parameters increased the centrifugal nozzle’s atomization cone angle and mass flow rate by 1.86% and 27.4%, respectively.
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基于响应面法(RSM)的拉瓦尔氢气喷嘴优化设计
为了深入研究气体燃料的喷射特性,对喷嘴的结构参数进行了优化。利用响应面法(RSM),本研究选择了入口半径 R1、出口半径 R2、喉直半径 R0、膨胀半角 θ 和收缩半角 α 作为设计参数。根据验证的数值模型,建立了出口速度 v 和质量流量 Q 的响应面预测模型。利用推导出的表达式,分析了设计变量对响应变量的贡献和交互影响。结果表明,出口半径和喉管半径对出口速度有显著影响。出口半径与出口速度呈正相关,而喉管半径与出口速度呈负相关。质量流量受喉管半径的影响最大,随着喉管半径的增大而增大。以出口速度和质量流量为优化目标,采用 MOGA 算法进行多目标优化。优化结果表明,优化后的结构参数使离心喷嘴的雾化锥角和质量流量分别提高了 1.86% 和 27.4%。
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