{"title":"基于计算流体动力学工具的陶瓷辊窑温度场均匀性粒子群优化","authors":"Wenbi Rao, Peng Li","doi":"10.1109/CINC.2009.99","DOIUrl":null,"url":null,"abstract":"In this paper ceramic roller kiln temperature field uniformity is mainly researched using computational fluid dynamics tools and particle swarm optimization (PSO). In consideration of burning and burning temperature control is key technique of burning regime, in order to produce quality product, it is very important to get the correct ceramic kiln design parameters by simulation model computation. The relationship between ceramic roller kiln simulation model building parameters and temperature field uniformity is preliminary researched in this paper, and particle swarm optimization is used based on the result of research and some feasible conclusion is draw for the peer review.","PeriodicalId":173506,"journal":{"name":"2009 International Conference on Computational Intelligence and Natural Computing","volume":"358 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Particle Swarm Optimization of Ceramic Roller Kiln Temperature Field Uniformity Using Computational Fluid Dynamics Tools\",\"authors\":\"Wenbi Rao, Peng Li\",\"doi\":\"10.1109/CINC.2009.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper ceramic roller kiln temperature field uniformity is mainly researched using computational fluid dynamics tools and particle swarm optimization (PSO). In consideration of burning and burning temperature control is key technique of burning regime, in order to produce quality product, it is very important to get the correct ceramic kiln design parameters by simulation model computation. The relationship between ceramic roller kiln simulation model building parameters and temperature field uniformity is preliminary researched in this paper, and particle swarm optimization is used based on the result of research and some feasible conclusion is draw for the peer review.\",\"PeriodicalId\":173506,\"journal\":{\"name\":\"2009 International Conference on Computational Intelligence and Natural Computing\",\"volume\":\"358 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2009.99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2009.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Particle Swarm Optimization of Ceramic Roller Kiln Temperature Field Uniformity Using Computational Fluid Dynamics Tools
In this paper ceramic roller kiln temperature field uniformity is mainly researched using computational fluid dynamics tools and particle swarm optimization (PSO). In consideration of burning and burning temperature control is key technique of burning regime, in order to produce quality product, it is very important to get the correct ceramic kiln design parameters by simulation model computation. The relationship between ceramic roller kiln simulation model building parameters and temperature field uniformity is preliminary researched in this paper, and particle swarm optimization is used based on the result of research and some feasible conclusion is draw for the peer review.