Estimation of fatigue S-N curves of welded joints using advanced probabilistic approach. (April 2017)

• Record Type: Journal Article
• Authors: D'Angelo, Luca; Nussbaumer, Alain
• Is Part Of: International journal of fatigue. Volume 97(2017)
• Page Start: 98
• Page End: 113
• Publication Date: 2017-04
• Subjects: Fatigue life -- S-N curves -- Maximum likelihood -- Monte-Carlo simulations; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2016.12.032
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: New probabilistic approach for estimation of characteristic S-N curves. Powerful tool for re-estimation of CA and VA S-N curves in current standards. Improved reliability in estimation of the CAFL. Improved reliability in estimation of S-N curve second slope. Improved reliability in estimation of critical damage sum at failure. Abstract: This paper provides a new advanced probabilistic approach for reliable estimation of the fatigue characteristic S-N curves of welded joints both for constant amplitude (CA) and variable amplitude (VA) loading conditions. The presented approach, which is referred to as the ML-MCS approach, combines Maximum Likelihood method (ML) and Monte-Carlo Simulations (MCS) method to estimate true p -quantiles of CA and VA S-N curves by using complete experimental data-sets. The ML-MCS approach includes a linearization method for use of S-N curves in combination with linear damage accumulation rule as well as for direct comparison with current standards. Application of the ML-MCS approach on two study cases and comparison with current standards shows that the use of the ML-MCS approach may have a significant impact in re-definition of CA and VA S-N curves of current standards and in particular of the CAFL, of the S-N curve second slope and of the critical value of accumulated damage at failure. The last section of the paper provides accurate guidelines for future experimental tests needed for re-definition of current standards.