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Sub-structure coupling for dynamic a...

Jensen, Hector.

Sub-structure coupling for dynamic analysisapplication to complex simulation-based problems involving uncertainty /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Sub-structure coupling for dynamic analysisby Hector Jensen, Costas Papadimitriou.
其他題名:	application to complex simulation-based problems involving uncertainty /
作者:	Jensen, Hector.
其他作者:	Papadimitriou, Costas.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xiii, 227 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Simulation methods.
電子資源:	https://doi.org/10.1007/978-3-030-12819-7
ISBN:	9783030128197$q(electronic bk.)

Sub-structure coupling for dynamic analysisapplication to complex simulation-based problems involving uncertainty /
Jensen, Hector.

Sub-structure coupling for dynamic analysisapplication to complex simulation-based problems involving uncertainty /[electronic resource] :by Hector Jensen, Costas Papadimitriou. - Cham :Springer International Publishing :2019. - xiii, 227 p. :ill., digital ;24 cm. - Lecture notes in applied and computational mechanics,v.891613-7736 ;. - Lecture notes in applied and computational mechanics ;v.61..

Model Reduction Techniques for Structural Dynamic Analyses -- Parametrization of Reduced-Order Models Based on Normal Modes -- Parametrization of Reduced-Order Models Based on Global Interface Reduction -- Reliability Analysis of Dynamical Systems -- Reliability Sensitivity Analysis of Dynamical Systems -- Reliability-Based Design Optimization -- Bayesian Finite Element Model Updating.

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. In this 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 reduced order models is sufficient to run the large number of dynamic re-analyses. Thus, a drastic reduction in computational effort is achieved without compromising the accuracy of the results. The capabilities of the developed procedures are demonstrated in a number of simulation-based problems involving uncertainty.

ISBN: 9783030128197$q(electronic bk.)

Standard No.: 10.1007/978-3-030-12819-7doi

CODEN: namm 22003373 a 450Subjects--Topical Terms:

185954
Simulation methods.

LC Class. No.: T57.62 / .J46 2019

Dewey Class. No.: 511.8

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