{"title":"基于非线性BT-POD模型约简的有限元模型几何参数快速扫描","authors":"Wei Wang, M. Vouvakis","doi":"10.1109/APS.2011.5997024","DOIUrl":null,"url":null,"abstract":"A finite element method (FEM) model-order reduction (MOR) methodology for the fast parametric sweep of geometrical features is presented. The proposed method first linearizes the otherwise non-linear FEM matrix dependence with respect to the geometry variation, and then uses a uniformly sampled balanced truncation proper orthogonal decomposition (BT-POD) reduction algorithm to expediently sweep over the parametric geometry space. The approach avoids slow re-meshing and full matrix reassembly by using mesh morphing approaches. Moreover, BT-POD is known to provide close to optimal size reduced problems using only a small number of samples, thus minimizing the the number of full-model solutions. Numerical results on two large-scale filter design examples are used to study the accuracy and efficiency of the proposed method.","PeriodicalId":6449,"journal":{"name":"2011 IEEE International Symposium on Antennas and Propagation (APSURSI)","volume":"31 1","pages":"2472-2475"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Fast geometric parameter sweep of FEM models via a nonlinear BT-POD model reduction\",\"authors\":\"Wei Wang, M. Vouvakis\",\"doi\":\"10.1109/APS.2011.5997024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A finite element method (FEM) model-order reduction (MOR) methodology for the fast parametric sweep of geometrical features is presented. The proposed method first linearizes the otherwise non-linear FEM matrix dependence with respect to the geometry variation, and then uses a uniformly sampled balanced truncation proper orthogonal decomposition (BT-POD) reduction algorithm to expediently sweep over the parametric geometry space. The approach avoids slow re-meshing and full matrix reassembly by using mesh morphing approaches. Moreover, BT-POD is known to provide close to optimal size reduced problems using only a small number of samples, thus minimizing the the number of full-model solutions. Numerical results on two large-scale filter design examples are used to study the accuracy and efficiency of the proposed method.\",\"PeriodicalId\":6449,\"journal\":{\"name\":\"2011 IEEE International Symposium on Antennas and Propagation (APSURSI)\",\"volume\":\"31 1\",\"pages\":\"2472-2475\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Symposium on Antennas and Propagation (APSURSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APS.2011.5997024\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Symposium on Antennas and Propagation (APSURSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APS.2011.5997024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast geometric parameter sweep of FEM models via a nonlinear BT-POD model reduction
A finite element method (FEM) model-order reduction (MOR) methodology for the fast parametric sweep of geometrical features is presented. The proposed method first linearizes the otherwise non-linear FEM matrix dependence with respect to the geometry variation, and then uses a uniformly sampled balanced truncation proper orthogonal decomposition (BT-POD) reduction algorithm to expediently sweep over the parametric geometry space. The approach avoids slow re-meshing and full matrix reassembly by using mesh morphing approaches. Moreover, BT-POD is known to provide close to optimal size reduced problems using only a small number of samples, thus minimizing the the number of full-model solutions. Numerical results on two large-scale filter design examples are used to study the accuracy and efficiency of the proposed method.