Experimental Determination of Uncertainty Importances for Monotonic Systems

Abstract

A system is called monotonic if its output (i.e., performance characteristic) is either increasing or decreasing with respect to any of the input variables (i.e., system parameters). For such systems, an experimental method is introduced to assess the effect of the uncertainty of an input variable on the uncertainty of the output, and thus, to determine relative criticalities of input uncertainties. An analysis method is also introduced to predict the percentage reduction in the uncertainty of the output when the uncertainty of an input or of a group of two inputs is reduced. The proposed method is computationally economical, especially for large-sized problems.