Title Sub-structure coupling for dynamic analysis : application to complex simulation-based problems involving uncertainty / Hector Jensen, Costas Papadimitriou

Published Cham, Switzerland : Springer, [2019]

Click on the following:
Springer eBooks
Springer Engineering eBooks

Copies

Description 1 online resource Series Lecture notes in applied and computational mechanics ; volume 89 Lecture notes in applied and computational mechanics ; v. 89. Contents Intro; Preface; Acknowledgements; Contents; Reduced-Order Models; 1 Model Reduction Techniques for Structural Dynamic Analyses; 1.1 Structural Model; 1.2 Substructure Modes; 1.2.1 Fixed-Interface Normal Modes; 1.2.2 Interface Constraint Modes; 1.3 Reduced-Order Model: Standard Formulation; 1.3.1 Transformation Matrix; 1.3.2 Reduced-Order Matrices; 1.4 Reduced-Order Model: Improved Formulation; 1.4.1 Static Correction; 1.4.2 Improved Transformation Matrix; 1.4.3 Enhanced Reduced-Order Matrices; 1.4.4 Remarks on the Use of Residual Modes; 1.5 Numerical Implementation: Pseudo-Code No. 1 1.6 Global Interface Reduction1.6.1 Interface Modes; 1.6.2 Reduced-Order Matrices Based on Dominant Fixed-Interface Modes; 1.6.3 Reduced-Order Matrices Based on Residual Fixed-Interface Modes; 1.7 Numerical Implementation: Pseudo-Code No. 2; 1.8 Local Interface Reduction; 1.9 Numerical Implementation: Pseudo-Code No. 3; 1.10 Reduced-Order Model Response; References; 2 Parametrization of Reduced-Order Models Based on Normal Modes; 2.1 Motivation; 2.2 Parametrization Scheme; 2.2.1 Substructure Matrices; 2.2.2 Normal Modes and Interface Constraint Modes 2.3 Parametrization of Reduced-Order Matrices2.3.1 Unreduced Matrices; 2.3.2 Transformation Matrix TD; 2.3.3 Reduced-Order Matrices D and D; 2.3.4 Transformation Matrix TR; 2.3.5 Reduced-Order Matrices R and R; 2.3.6 Expansion of R and R Under Partial Invariant Conditions of TR; 2.4 Numerical Implementation: Pseudo-Code No. 4; References; 3 Parametrization of Reduced-Order Models Based on Global Interface Reduction; 3.1 Meta-Model for Global Interface Modes; 3.1.1 Baseline Information; 3.1.2 Approximation of Interface Modes; 3.1.3 Determination of Interpolation Coefficients 3.1.4 Higher-Order Approximations3.1.5 Support Points; 3.2 Numerical Implementation: Pseudo-Code No. 5; 3.3 Reduced-Order Matrices Based on Global Interface Reduction; 3.3.1 Transformation Matrix TDI; 3.3.2 Reduced-Order Matrices DI and DI; 3.3.3 Transformation Matrix TRI; 3.3.4 Reduced-Order Matrices RI and RI; 3.3.5 Expansion of RI and RI Under Global Invariant Conditions of TRI; 3.4 Numerical Implementation: Pseudo-Code No. 6; 3.5 Treatment of Local Interface Modes; 3.6 Final Remarks; References; Application to Reliability Problems; 4 Reliability Analysis of Dynamical Systems 4.1 Motivation4.2 Reliability Problem Formulation; 4.3 Reliability Estimation; 4.3.1 General Remarks; 4.3.2 Basic Ideas; 4.3.3 Failure Probability Estimator; 4.4 Numerical Implementation; 4.4.1 Basic Implementation; 4.4.2 Implementation Issues; 4.5 Stochastic Model for Excitation; 4.5.1 General Description; 4.5.2 High-Frequency Components; 4.5.3 Pulse Components; 4.5.4 Synthesis of Near-Field Ground Motions; 4.5.5 Seismicity Model; 4.6 Application Problem No. 1; 4.6.1 Model Description and Substructures Characterization; 4.6.2 Reduced-Order Model Based on Dominant Fixed-Interface Normal Modes Summary 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 Bibliography Includes bibliographical references Notes Online resource; title from digital title page (viewed on April 08, 2019) Subject Simulation methods. simulation methods. Maths for scientists. Probability & statistics. Mechanics of solids. Computers -- Computer Science. Mathematics -- Probability & Statistics -- General. Science -- Mechanics -- Solids. Simulation methods Form Electronic book Author Papadimitriou, Costas, author ISBN 9783030128197 3030128199 9783030128203 3030128202 9783030128210 3030128210

  Permalink