Robust quantile regression analysis for probabilistic modelling of S-N curves

Abstract

The scatter in fatigue data is commonly characterized by probability distributions for constructing the probabilistic S-N curves. However, there is notable estimation bias under distribution misspecification. In this paper, we proposed a quantile regression framework for modeling S-N curves. The quantile regression model can be built directly on the experimental data without any distribution assumption. Extensive simulations and two experimental datasets are used to illustrate the usefulness of the proposed model. The results demonstrate that the quantile regression model is exempt from the problem of incorrectly specifying the potential fatigue life distribution and is robust to the non-constant scale problem.