{"title":"基于响应面法(RSM)的拉瓦尔氢气喷嘴优化设计","authors":"Jianyang Fang, Yusheng Ju, Liwei Mao, Shichao Pei","doi":"10.1088/1742-6596/2838/1/012035","DOIUrl":null,"url":null,"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 <italic toggle=\"yes\">R<sub>1</sub></italic>, outlet radius <italic toggle=\"yes\">R<sub>2</sub></italic>, throat straight radius <italic toggle=\"yes\">R<sub>0</sub></italic>, expansion half angle <italic toggle=\"yes\">θ</italic>, and contraction half angle <italic toggle=\"yes\">α</italic> as design parameters. Based on the validated numerical model, a response surface prediction model for outlet velocity <italic toggle=\"yes\">v</italic> and mass flow rate <italic toggle=\"yes\">Q</italic> 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.","PeriodicalId":16821,"journal":{"name":"Journal of Physics: Conference Series","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization design of hydrogen Laval nozzle based on response surface methodology (RSM)\",\"authors\":\"Jianyang Fang, Yusheng Ju, Liwei Mao, Shichao Pei\",\"doi\":\"10.1088/1742-6596/2838/1/012035\",\"DOIUrl\":null,\"url\":null,\"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 <italic toggle=\\\"yes\\\">R<sub>1</sub></italic>, outlet radius <italic toggle=\\\"yes\\\">R<sub>2</sub></italic>, throat straight radius <italic toggle=\\\"yes\\\">R<sub>0</sub></italic>, expansion half angle <italic toggle=\\\"yes\\\">θ</italic>, and contraction half angle <italic toggle=\\\"yes\\\">α</italic> as design parameters. Based on the validated numerical model, a response surface prediction model for outlet velocity <italic toggle=\\\"yes\\\">v</italic> and mass flow rate <italic toggle=\\\"yes\\\">Q</italic> 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.\",\"PeriodicalId\":16821,\"journal\":{\"name\":\"Journal of Physics: Conference Series\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Physics: Conference Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1088/1742-6596/2838/1/012035\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Physics: Conference Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1088/1742-6596/2838/1/012035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization design of hydrogen Laval nozzle based on response surface methodology (RSM)
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.