Parametric probabilistic model for predicting creep remaining useful life
Résumé
The creep phenomenon, associated with a time-dependent progressive deformation of a material under stress and high temperatures, is of great industrial interest since these are typical operating conditions in several industries. Thus, a safe forecast of the life in creep is a critical phase in the design of equipment that operates at high temperatures, essential for the success of these projects. Although several parametric methods are available to quantify the creep deformation, most of them use deterministic approaches, that do not consider the remarkable dispersion of experimental creep data. This inevitably leads to deterioration in the predictive capacity of these models. Aiming to correct this deficiency, this work employs a parametric probabilistic approach to quantify the uncertainties associated with the parameters of parametric models for predicting creep remaining life. A probabilistic model, constructed with aid of the statistical information extracted from experimental data, is used to describe the underlying parametric uncertainties, and Monte Carlo method is used to propagate these uncertainties through the predictive model. From that, it is possible to evaluate the forecasting capacity of each model and define safe limits with known confidence levels.
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