{"title":"基于混合粒子群算法的钢连铸二冷区对流换热系数参数识别","authors":"Guoshan Wu, Rong-Yang Wu","doi":"10.1109/CIMA.2005.1662305","DOIUrl":null,"url":null,"abstract":"Solidification model is developed based on control volume method for steel continuous casting process, which is nonlinear and non-differential, and parameters of convective heat transfer coefficient for each segment of the secondary cooling zone are ascertained, a new hybrid particle swarm algorithm (CPSO) is introduced to improve the optimizing performance by embedding the chaotic search in the particles swarm algorithm. It is used to identify the convective heat transfer coefficients according to billet surface temperature and shell thickness. Compared with the empirical formula method, it has a better agreement with trail data","PeriodicalId":306045,"journal":{"name":"2005 ICSC Congress on Computational Intelligence Methods and Applications","volume":"117 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Identification of convection heat transfer coefficient parameters based on hybrid particle swarm algorithm in the secondary cooling zone for steel continuous casting process\",\"authors\":\"Guoshan Wu, Rong-Yang Wu\",\"doi\":\"10.1109/CIMA.2005.1662305\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Solidification model is developed based on control volume method for steel continuous casting process, which is nonlinear and non-differential, and parameters of convective heat transfer coefficient for each segment of the secondary cooling zone are ascertained, a new hybrid particle swarm algorithm (CPSO) is introduced to improve the optimizing performance by embedding the chaotic search in the particles swarm algorithm. It is used to identify the convective heat transfer coefficients according to billet surface temperature and shell thickness. Compared with the empirical formula method, it has a better agreement with trail data\",\"PeriodicalId\":306045,\"journal\":{\"name\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"volume\":\"117 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 ICSC Congress on Computational Intelligence Methods and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIMA.2005.1662305\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 ICSC Congress on Computational Intelligence Methods and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIMA.2005.1662305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of convection heat transfer coefficient parameters based on hybrid particle swarm algorithm in the secondary cooling zone for steel continuous casting process
Solidification model is developed based on control volume method for steel continuous casting process, which is nonlinear and non-differential, and parameters of convective heat transfer coefficient for each segment of the secondary cooling zone are ascertained, a new hybrid particle swarm algorithm (CPSO) is introduced to improve the optimizing performance by embedding the chaotic search in the particles swarm algorithm. It is used to identify the convective heat transfer coefficients according to billet surface temperature and shell thickness. Compared with the empirical formula method, it has a better agreement with trail data