Global sensitivity is used to quantify the influence of uncertain model inputs on the output variability of static models in general.\nHowever, very few approaches can be applied for the sensitivity analysis of long-term degeneracy models, as far as time-dependent\nreliability is concerned. The reason is that the static sensitivity may not reflect the completed sensitivity during the entire life\ncircle. This paper presents time-dependent global sensitivity analysis for long-term degeneracy models based on polynomial chaos\nexpansion (PCE). Sobol� indices are employed as the time-dependent global sensitivity since they provide accurate information on\nthe selected uncertain inputs. In order to compute Sobol� indices more efficiently, this paper proposes a moving least squares (MLS)\nmethod to obtain the time-dependent PCE coefficients with acceptable simulation effort. Then Sobol� indices can be calculated\nanalytically as a postprocessing of the time-dependent PCE coefficients with almost no additional cost. A test case is used to\nshow how to conduct the proposed method, then this approach is applied to an engineering case, and the time-dependent global\nsensitivity is obtained for the long-term degeneracy mechanism model.
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