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Model-reduction techniques for reliability-based design problems of complex structural systems

Author

Listed:
  • Jensen, H.A.
  • Muñoz, A.
  • Papadimitriou, C.
  • Millas, E.

Abstract

This work presents a strategy for dealing with reliability-based design problems of a class of linear and nonlinear finite element models under stochastic excitation. In general, the solution of this class of problems is computationally very demanding due to the large number of finite element model analyses required during the design process. A model reduction technique combined with an appropriate optimization scheme is proposed to carry out the design process efficiently in a reduced space of generalized coordinates. In particular, a method based on component mode synthesis is implemented to define a reduced-order model for the structural system. The re-analyses of the component or substructure modes as well as the re-assembling of the reduced-order system matrices due to changes in the values of the design variables are avoided. The effectiveness of the proposed model reduction technique in the context of reliability-based design problems is demonstrated by two numerical examples.

Suggested Citation

  • Jensen, H.A. & Muñoz, A. & Papadimitriou, C. & Millas, E., 2016. "Model-reduction techniques for reliability-based design problems of complex structural systems," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 204-217.
    • Handle: RePEc:eee:reensy:v:149:y:2016:i:c:p:204-217
    DOI: 10.1016/j.ress.2016.01.003
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    References listed on IDEAS

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    1. Norbert Kuschel & Rüdiger Rackwitz, 1997. "Two basic problems in reliability-based structural optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 46(3), pages 309-333, October.
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    Cited by:

    1. Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan, 2017. "A newly formulated resilience measure that considers false alarms," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 417-427.
    2. Li, Jin-Yang & Lu, Jubin & Zhou, Hao, 2023. "Reliability analysis of structures with inerter-based isolation layer under stochastic seismic excitations," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Yoo, Minji & Kim, Taejin & Yoon, Joung Taek & Kim, Yunhan & Kim, Sooho & Youn, Byeng D., 2020. "A resilience measure formulation that considers sensor faults," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    4. Li, Jian & Dueñas-Osorio, Leonardo & Chen, Changkun & Shi, Congling, 2016. "Connectivity reliability and topological controllability of infrastructure networks: A comparative assessment," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 24-33.
    5. Jensen, H.A. & Esse, C. & Araya, V. & Papadimitriou, C., 2017. "Implementation of an adaptive meta-model for Bayesian finite element model updating in time domain," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 174-190.
    6. Jensen, H.A. & Mayorga, F. & Valdebenito, M. & Chen, J., 2020. "An effective parametric model reduction technique for uncertainty propagation analysis in structural dynamics," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    7. Å nipas, Mindaugas & Radziukynas, Virginijus & ValakeviÄ ius, Eimutis, 2018. "Numerical solution of reliability models described by stochastic automata networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 570-578.

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