Eventos Anais de eventos
COBEM 2021
26th International Congress of Mechanical Engineering
Parametric probabilistic models for predicting creep remaining useful life
Submission Author:
Victor Maudonet , RJ , Brazil
Co-Authors:
Victor Maudonet, Americo Barbosa da Cunha Junior, Carlos Frederico Trotta Matt
Presenter: Victor Maudonet
doi://10.26678/ABCM.COBEM2021.COB2021-2312
Abstract
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 the life in creep is a critical phase in the design of equipments that operates at high temperatures. When recognizing this problem, a detailed understanding of creep is essential for the success of these projects. With this objective, several parametric methods were created to quantify the creep deformation in high temperature applications. However, most of them use a deterministic approach and do not consider the remarkable dispersion of experimental creep data. In this sense, this work adopted a parametric probabilistic approach to quantify the uncertainties associated with the parameters of parametric models for predicting creep remaining life. 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 model parameters. The input parameters have a joint Gaussian distribution and the output parameter, the rupture time, has an exponential distribution evidencing the great dispersion associated with this parameter and the need for an investigation under a probabilistic perspective. From that, it is possible to evaluate the forecasting capacity of each model and define safe limits with known confidence levels. In addition, in presenting this application of the complete uncertainty quantification framework, the goal is to promote broader application and acceptance within the international structural integrity community of methodologies for conducting probabilistic assessments in creep.
Keywords
Creep, structural integrity, uncertainty quantification, Probabilistic framework, Monte Carlo method
