{"title":"基于Jacobi-Davidson迭代的雷达截面降阶有限元模型","authors":"N. Kumar, K. Vinoy, S. Gopalakrishnan","doi":"10.1109/AEMC.2013.7045048","DOIUrl":null,"url":null,"abstract":"Finite element modeling of large-scale scattering problems like radar cross-section (RCS) lead to large matrices. Model order reduction (MOR) using eigenspace projection of these models involving plane wave excitation requires solution of nonlinear eigenvalue problems. This paper proposes a methodology to expediently compute wideband RCS. Jacobi-Davidson iteration is used to generate the projection spaces. Reduction by many orders in the system size and the computational cost is exemplified.","PeriodicalId":169237,"journal":{"name":"2013 IEEE Applied Electromagnetics Conference (AEMC)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Jacobi-Davidson iteration based reduced order finite element models for radar cross-section\",\"authors\":\"N. Kumar, K. Vinoy, S. Gopalakrishnan\",\"doi\":\"10.1109/AEMC.2013.7045048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Finite element modeling of large-scale scattering problems like radar cross-section (RCS) lead to large matrices. Model order reduction (MOR) using eigenspace projection of these models involving plane wave excitation requires solution of nonlinear eigenvalue problems. This paper proposes a methodology to expediently compute wideband RCS. Jacobi-Davidson iteration is used to generate the projection spaces. Reduction by many orders in the system size and the computational cost is exemplified.\",\"PeriodicalId\":169237,\"journal\":{\"name\":\"2013 IEEE Applied Electromagnetics Conference (AEMC)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE Applied Electromagnetics Conference (AEMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEMC.2013.7045048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Applied Electromagnetics Conference (AEMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEMC.2013.7045048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Jacobi-Davidson iteration based reduced order finite element models for radar cross-section
Finite element modeling of large-scale scattering problems like radar cross-section (RCS) lead to large matrices. Model order reduction (MOR) using eigenspace projection of these models involving plane wave excitation requires solution of nonlinear eigenvalue problems. This paper proposes a methodology to expediently compute wideband RCS. Jacobi-Davidson iteration is used to generate the projection spaces. Reduction by many orders in the system size and the computational cost is exemplified.