Modeling metallic fatigue data using the Birnbaum--Saunders distribution

arXiv (Cornell University)

Abstract

This work employs the Birnbaum--Saunders distribution to model the fatigue life of metallic materials under cyclic loading and compares it with the normal distribution. Fatigue-limit models are fitted to three datasets of unnotched specimens of 75S-T6 aluminum alloys and carbon laminate with different loading types. A new equivalent stress definition that accounts for the effect of the experiment type is proposed. The results show that the Birnbaum--Saunders distribution consistently outperforms the normal distribution in fitting the fatigue data and provides more accurate predictions of fatigue life and survival probability.

Authors 3

1. Zaid Sawlan

   King Fahd University of Petroleum and Minerals

   Affiliation as printed

   Department of Mathematics , King Fahd University of Petroleum and Minerals , Dhahran , Saudi Arabia

2. Marco Scavino

   Universidad de la República de Uruguay

   Affiliation as printed

   Instituto de Estadística (IESTA) , Universidad de la República , Montevideo , Uruguay

3. Raul F. Tempone Aachen Chair of Mathematics for Uncertainty Quantification

   RWTH Aachen University · King Abdullah University of Science and Technology

   Affiliation as printed

   CEMSE , King Abdullah University of Science and Technology , Thuwal , Saudi Arabia

   Chair of Mathematics for Uncertainty Quantification , RWTH Aachen University , Aachen , Germany