Abstract
In the field of uncertainty quantification (UQ), propagation of uncertainty is one of the most important tasks, as it is essential to almost all UQ analysis. While many numerical methods have been developed for uncertainty propagation in probabilistic framework, much less has been discussed in the nonprobabilistic framework, which is important whenever one does not possess sufficient data or knowledge of the underlying systems. In this paper, we focus on the use of fuzzy sets to model uncertainty and their propagation through physical systems. In particular, we develop a numerical strategy that can efficiently propagate fuzzy sets in complex systems. The method utilizes an accurate approximation model for the solution over the support of the input fuzzy sets and then retrieves the output fuzzy set information via the approximation model. By doing so the method becomes highly efficient, as the only simulation cost is in the construction of the approximation model. In particular, we discuss the use of ortho...
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