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.
|Journal||ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering|
|State||Published - Jun 2021|