Sub-structure Coupling for Dynamic Analysis

Application to Complex Simulation-Based Problems Involving Uncertainty

  • Hector Jensen
  • Costas Papadimitriou

Part of the Lecture Notes in Applied and Computational Mechanics book series (LNACM, volume 89)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Reduced-Order Models

    1. Front Matter
      Pages 1-1
    2. Hector Jensen, Costas Papadimitriou
      Pages 3-31
    3. Hector Jensen, Costas Papadimitriou
      Pages 33-47
    4. Hector Jensen, Costas Papadimitriou
      Pages 49-65
  3. Application to Reliability Problems

    1. Front Matter
      Pages 67-67
    2. Hector Jensen, Costas Papadimitriou
      Pages 69-111
    3. Hector Jensen, Costas Papadimitriou
      Pages 113-141
    4. Hector Jensen, Costas Papadimitriou
      Pages 143-176
  4. Application to Identification Problems

    1. Front Matter
      Pages 177-177
    2. Hector Jensen, Costas Papadimitriou
      Pages 179-227

About this book


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.


Structural Dynamic Analysis Uncertainty Quantification Structural Dynamic Simulation Reliability Analysis Reliability Sensitivity Reliability Optimization Model Reduction Techniques Computational Mechanics

Authors and affiliations

  • Hector Jensen
    • 1
  • Costas Papadimitriou
    • 2
  1. 1.Federico Santa María Technical UniversityValparaisoChile
  2. 2.University of ThessalyVolosGreece

Bibliographic information

  • DOI
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-030-12818-0
  • Online ISBN 978-3-030-12819-7
  • Series Print ISSN 1613-7736
  • Series Online ISSN 1860-0816
  • Buy this book on publisher's site
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