{"title":"瞬态弹性动力学中的随机不确定性建模","authors":"Christian Soize","doi":"10.1016/S1620-7742(01)01307-1","DOIUrl":null,"url":null,"abstract":"<div><p>A new nonparametric probabilistic approach is presented for modeling random uncertainties in transient linear elastodynamics. The information used does not require a description of the local parameters of the mechanical model. The probability model is constructed in the generalized coordinates associated with the elastic eigenmodes. The available information is constituted of the algebraic properties of the generalized mass, damping and stiffness matrices which have to be positive-definite symmetric matrices, and the knowledge of these matrices for the mean reduced matrix model. The convergence of the stochastic solution with respect to the dimension of the random reduced matrix model is analysed.</p></div>","PeriodicalId":100302,"journal":{"name":"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics","volume":"329 3","pages":"Pages 225-230"},"PeriodicalIF":0.0000,"publicationDate":"2001-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1620-7742(01)01307-1","citationCount":"2","resultStr":"{\"title\":\"Modélisation des incertitudes aléatoires en élastodynamique transitoire\",\"authors\":\"Christian Soize\",\"doi\":\"10.1016/S1620-7742(01)01307-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>A new nonparametric probabilistic approach is presented for modeling random uncertainties in transient linear elastodynamics. The information used does not require a description of the local parameters of the mechanical model. The probability model is constructed in the generalized coordinates associated with the elastic eigenmodes. The available information is constituted of the algebraic properties of the generalized mass, damping and stiffness matrices which have to be positive-definite symmetric matrices, and the knowledge of these matrices for the mean reduced matrix model. The convergence of the stochastic solution with respect to the dimension of the random reduced matrix model is analysed.</p></div>\",\"PeriodicalId\":100302,\"journal\":{\"name\":\"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics\",\"volume\":\"329 3\",\"pages\":\"Pages 225-230\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S1620-7742(01)01307-1\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1620774201013071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1620774201013071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modélisation des incertitudes aléatoires en élastodynamique transitoire
A new nonparametric probabilistic approach is presented for modeling random uncertainties in transient linear elastodynamics. The information used does not require a description of the local parameters of the mechanical model. The probability model is constructed in the generalized coordinates associated with the elastic eigenmodes. The available information is constituted of the algebraic properties of the generalized mass, damping and stiffness matrices which have to be positive-definite symmetric matrices, and the knowledge of these matrices for the mean reduced matrix model. The convergence of the stochastic solution with respect to the dimension of the random reduced matrix model is analysed.