Quantificação de incertezas em modelos paramétricos de previsão de vida em fluência

Abstract

In industry, materials are often used in service at high temperatures and under mechanical stress. A progressive deformation, depending on time, of a material under stress and high temperatures is called creep. This phenomenon is of great industrial interest and a safe forecast of creep life is a critical phase in the design of equipment that operates at high temperatures. When recognizing this problem, a detailed understanding of creep is essential for the success of these projects, ensuring that components do not undergo excessive deformation which can lead to failure. From this perspective, several parametric methods were developed to quantify the creep deformation in high temperature applications. However, most of them uses a deterministic approach and does not rigorously consider the remarkable dispersion of experimental creep data. The current work adopts a parametric probabilistic approach to quantify the uncertainties associated with the input parameters of parametric models developed for predicting creep rupture time. Based on the statistical information extracted from the experimental data, a theoretical uncertainty quantification framework based on Monte Carlo simulations was applied to determine the probability distribution of the quantity of interest. Afterwards, one evaluates the forecasting capability of each model and defines safe limits with known confidence levels. Another goal is to disclose the probabilistic framework developed in this work to promote broader application within the international research community on structural integrity assessment for quantifying the uncertainties associated with creep.