| 書目名稱 | Sub-structure Coupling for Dynamic Analysis | | 副標(biāo)題 | Application to Compl | | 編輯 | Hector Jensen,Costas Papadimitriou | | 視頻video | http://file.papertrans.cn/882/881232/881232.mp4 | | 概述 | Provides a thorough treatment of a class of model reduction techniques for structural dynamical systems.Includes applications to simulation-based problems such as reliability analysis, reliability sen | | 叢書名稱 | Lecture Notes in Applied and Computational Mechanics | | 圖書封面 |  | | 描述 | .This book combines a model reduction technique with an efficient parametrization scheme for the purpose of solving a class of complex and computationally expensive simulation-based problems involving finite element models. These problems, which have a wide range of important applications in several engineering fields, include reliability analysis, structural dynamic simulation, sensitivity analysis, reliability-based design optimization, Bayesian model validation, uncertainty quantification and propagation, etc. ?The solution of this type of problems requires a large number of dynamic re-analyses. To cope with this difficulty, a model reduction technique known as substructure coupling for dynamic analysis is considered. While the use of reduced order models alleviates part of the computational effort, their repetitive generation during the simulation processes can be computational expensive due to the substantial computational overhead that arises at the substructure level. Inthis regard, an efficient finite element model parametrization scheme is considered. ?When the division of the structural model is guided by such a parametrization scheme, the generation of a small number of | | 出版日期 | Book 2019 | | 關(guān)鍵詞 | Structural Dynamic Analysis; Uncertainty Quantification; Structural Dynamic Simulation; Reliability Ana | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-12819-7 | | isbn_softcover | 978-3-030-12821-0 | | isbn_ebook | 978-3-030-12819-7Series ISSN 1613-7736 Series E-ISSN 1860-0816 | | issn_series | 1613-7736 | | copyright | Springer Nature Switzerland AG 2019 |
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