Fatigue Life Distribution Estimation  
Author D. Gary Harlow

 

Co-Author(s)

 

Abstract Modeling fatigue life is a complex task. Uncertainty cannot be eliminated due to microstructural variability, manufacturing processing, approximate scientific modeling, and experimental inconsistencies. Uncertainty is enhanced extreme life estimation because those events are rare. There is limited data for low stress levels in stress–life testing where lives are much longer. There is frequently over an order of magnitude difference in fatigue lives in that region. The primary purpose of this paper is to propose an empirically based methodology for estimating the cumulative distribution functions for fatigue life, given the applied stress. The methodology incorporates available fatigue life data for various stresses using a statistical transformation to merge the life data so that the distribution estimation is more accurate than traditional stress–life approaches. To assess the validity of the proposed methodology confidence bounds are estimated for the stress–life data. The development of the methodology and its subsequent validation is illustrated using extensive fatigue life data for 2024–T4 aluminum alloy specimens readily available in the open literature.

 

Keywords Fatigue, Fatigue life transformation, Life estimation, Lower tail behavior, Weibull distribution
   
    Article #:  RQD25-10
 
Proceedings of 25th ISSAT International Conference on Reliability & Quality in Design
August 1-3, 2019 - Las Vegas, NV, U.S.A.