{"title":"预测材料不确定性对有限元散射计算影响的Kriging方法","authors":"S. Kasdorf, J. Harmon, B. Notaroš","doi":"10.1109/USNC-URSI52151.2023.10238252","DOIUrl":null,"url":null,"abstract":"We present a Kriging interpolation surrogate function for use in reconstruction of probability density function in scattering uncertainty quantification problems, focusing on predicting material uncertainty impact on finite-element scattering computations. The results show extremely high reconstruction accuracy while reducing computation time by approximately two orders of magnitude relative to the conventional Monte Carlo approach. This tool offers a robust option for future uncertainty quantification problems in the field of computational electro magnetics.","PeriodicalId":383636,"journal":{"name":"2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Kriging Methodology for Predicting Material Uncertainty Impact on FEM Scattering Computations\",\"authors\":\"S. Kasdorf, J. Harmon, B. Notaroš\",\"doi\":\"10.1109/USNC-URSI52151.2023.10238252\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a Kriging interpolation surrogate function for use in reconstruction of probability density function in scattering uncertainty quantification problems, focusing on predicting material uncertainty impact on finite-element scattering computations. The results show extremely high reconstruction accuracy while reducing computation time by approximately two orders of magnitude relative to the conventional Monte Carlo approach. This tool offers a robust option for future uncertainty quantification problems in the field of computational electro magnetics.\",\"PeriodicalId\":383636,\"journal\":{\"name\":\"2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/USNC-URSI52151.2023.10238252\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (USNC-URSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/USNC-URSI52151.2023.10238252","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Kriging Methodology for Predicting Material Uncertainty Impact on FEM Scattering Computations
We present a Kriging interpolation surrogate function for use in reconstruction of probability density function in scattering uncertainty quantification problems, focusing on predicting material uncertainty impact on finite-element scattering computations. The results show extremely high reconstruction accuracy while reducing computation time by approximately two orders of magnitude relative to the conventional Monte Carlo approach. This tool offers a robust option for future uncertainty quantification problems in the field of computational electro magnetics.