Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
775488 | International Journal of Fatigue | 2011 | 10 Pages |
Abstract
In this work, a novel approach to fatigue life prediction under step-stress conditions is introduced, where the cumulative distribution function for the failure of components was implemented by means of a neural network. The model was fit to experimental data on the fatigue life of steel under step-stress conditions. For comparison, a standard approach based on the lognormal distribution function was also implemented and fit to the same experimental data. Both models were optimized by evolutionary computation, using a maximum likelihood estimator. The Kolmogorov–Smirnov test was applied to compare the results of the new approach to those obtained with the lognormal distribution function.
Related Topics
Physical Sciences and Engineering
Engineering
Mechanical Engineering
Authors
João Carlos Figueira Pujol, João Mário Andrade Pinto,