Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems

Marcos A. Valdebenito, Hector A. Jensen, Pengfei Wei, Michael Beer, Andre T. Beck

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


This contribution proposes a strategy for performing fuzzy analysis of linear static systems applying a-level optimization. In order to decrease numerical costs, full system analyses are replaced by a reduced order model that projects the equilibrium equations to a small-dimensional space. The basis associated with the reduced order model is constructed by means of a single analysis of the system plus a sensitivity analysis. This reduced basis is enriched as the a-level optimization strategy progresses in order to protect the quality of the approximations provided by the reduced order model. A numerical example shows that with the proposed strategy, it is possible to produce an accurate estimate of the membership function of the response of the system with a limited number of full system analyses.

Original languageEnglish
Article number020904
JournalASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Issue number2
StatePublished - Jun 2021
Externally publishedYes


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