{"title":"基于双拉丁超立方采样法的NESTOR功率分布不确定性分析","authors":"Hongkuan Liao, Qing Li, Yingrui Yu, Yuying Hu, L. Wu, Chenlin Wang, Jinyu Wang, Jinghui Wang, Peng Xiao","doi":"10.1115/ICONE26-81441","DOIUrl":null,"url":null,"abstract":"Due to the complexity of the reactor system, many approximations are used in the nuclear design and calculations inevitably. The accuracy of the nuclear design software is closely related to the safety of the reactor design and operation. Besides, improving the accuracy is an effective way to excavating the economy of nuclear power plants. To analyze the uncertainty of power distribution for NESTOR nuclear design software, we suggested an uncertainty analysis method based on the double Latin Hypercube Sampling (LHS) method and the random sampling statistical analysis (RSSA) method, and built an uncertainty analysis process based on LHS. The uncertainty of physical model and the uncertainty of the change of parameters were both taken into consideration with the double samplings, and 3481 core states were generated by the double samplings. Therefore, the uncertainty of power distribution could be directly analyzed through modeling computation, and the uncertainty of radial power distribution was achieved as ±3.856% under the condition of 95% confidence coefficient and 95% probability. Meanwhile, according to deviation transmission idea, we obtained the uncertainty of power distribution from physical models and the change of parameters based on the measured method. The result shows that the accuracy using the double sampling method is nearly the same to which achieved by the deviation transmission idea, and more conservative.","PeriodicalId":394688,"journal":{"name":"Volume 4: Nuclear Safety, Security, and Cyber Security; Computer Code Verification and Validation","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Uncertainty Analysis of Power Distribution for NESTOR Based on the Double Latin Hypercube Sampling Method\",\"authors\":\"Hongkuan Liao, Qing Li, Yingrui Yu, Yuying Hu, L. Wu, Chenlin Wang, Jinyu Wang, Jinghui Wang, Peng Xiao\",\"doi\":\"10.1115/ICONE26-81441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the complexity of the reactor system, many approximations are used in the nuclear design and calculations inevitably. The accuracy of the nuclear design software is closely related to the safety of the reactor design and operation. Besides, improving the accuracy is an effective way to excavating the economy of nuclear power plants. To analyze the uncertainty of power distribution for NESTOR nuclear design software, we suggested an uncertainty analysis method based on the double Latin Hypercube Sampling (LHS) method and the random sampling statistical analysis (RSSA) method, and built an uncertainty analysis process based on LHS. The uncertainty of physical model and the uncertainty of the change of parameters were both taken into consideration with the double samplings, and 3481 core states were generated by the double samplings. Therefore, the uncertainty of power distribution could be directly analyzed through modeling computation, and the uncertainty of radial power distribution was achieved as ±3.856% under the condition of 95% confidence coefficient and 95% probability. Meanwhile, according to deviation transmission idea, we obtained the uncertainty of power distribution from physical models and the change of parameters based on the measured method. The result shows that the accuracy using the double sampling method is nearly the same to which achieved by the deviation transmission idea, and more conservative.\",\"PeriodicalId\":394688,\"journal\":{\"name\":\"Volume 4: Nuclear Safety, Security, and Cyber Security; Computer Code Verification and Validation\",\"volume\":\"97 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 4: Nuclear Safety, Security, and Cyber Security; Computer Code Verification and Validation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/ICONE26-81441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 4: Nuclear Safety, Security, and Cyber Security; Computer Code Verification and Validation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/ICONE26-81441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Uncertainty Analysis of Power Distribution for NESTOR Based on the Double Latin Hypercube Sampling Method
Due to the complexity of the reactor system, many approximations are used in the nuclear design and calculations inevitably. The accuracy of the nuclear design software is closely related to the safety of the reactor design and operation. Besides, improving the accuracy is an effective way to excavating the economy of nuclear power plants. To analyze the uncertainty of power distribution for NESTOR nuclear design software, we suggested an uncertainty analysis method based on the double Latin Hypercube Sampling (LHS) method and the random sampling statistical analysis (RSSA) method, and built an uncertainty analysis process based on LHS. The uncertainty of physical model and the uncertainty of the change of parameters were both taken into consideration with the double samplings, and 3481 core states were generated by the double samplings. Therefore, the uncertainty of power distribution could be directly analyzed through modeling computation, and the uncertainty of radial power distribution was achieved as ±3.856% under the condition of 95% confidence coefficient and 95% probability. Meanwhile, according to deviation transmission idea, we obtained the uncertainty of power distribution from physical models and the change of parameters based on the measured method. The result shows that the accuracy using the double sampling method is nearly the same to which achieved by the deviation transmission idea, and more conservative.