東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Sub-structure coupling for dynamic a...

Jensen, Hector.

FindBook

Google Book

Amazon

博客來

Sub-structure coupling for dynamic analysis = application 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 analysis/ by 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.
內容註:	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.
Contained By:	Springer eBooks
標題:	Simulation methods. -
電子資源:	https://doi.org/10.1007/978-3-030-12819-7
ISBN:	9783030128197

Sub-structure coupling for dynamic analysis = application 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.89..

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

Standard No.: 10.1007/978-3-030-12819-7doiSubjects--Topical Terms:

581321
Simulation methods.

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

Dewey Class. No.: 511.8

Sub-structure coupling for dynamic analysis = application to complex simulation-based problems involving uncertainty /
LDR:03034nmm a2200337 a 4500 001 2180534
003 DE-He213
005 20190326202756.0
006 m d
007 cr nn 008maaau
008 191122s2019 gw s 0 eng d
020 $a 9783030128197 $q (electronic bk.)
020 $a 9783030128180 $q (paper)
024 7 $a 10.1007/978-3-030-12819-7 $2 doi
035 $a 978-3-030-12819-7
040 $a GP $c GP
041 0 $a eng
050 4 $a T57.62 $b .J46 2019
072 7 $a TGMD $2 bicssc
072 7 $a SCI096000 $2 bisacsh
072 7 $a TGMD $2 thema
082 0 4 $a 511.8 $2 23
090 $a T57.62 $b .J54 2019
100 1 $a Jensen, Hector. $3 3386695
245 1 0 $a Sub-structure coupling for dynamic analysis $h [electronic resource] : $b application to complex simulation-based problems involving uncertainty / $c by Hector Jensen, Costas Papadimitriou.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xiii, 227 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in applied and computational mechanics, $x 1613-7736 ; $v v.89
505 0 $a 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.
520 $a 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.
650 0 $a Simulation methods. $3 581321
650 1 4 $a Solid Mechanics. $3 3381524
650 2 4 $a Computational Science and Engineering. $3 893018
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
700 1 $a Papadimitriou, Costas. $3 2195111
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Lecture notes in applied and computational mechanics ; $v v.89. $3 3386696
856 4 0 $u https://doi.org/10.1007/978-3-030-12819-7
950 $a Engineering (Springer-11647)