Modeling Metallic Fatigue Data Using the Birnbaum–Saunders Distribution-Reference-Cited by-同舟云学术

Modeling Metallic Fatigue Data Using the Birnbaum–Saunders Distribution

Published:2024-04-26 Issue:5 Volume:14 Page:508
ISSN:2075-4701
Container-title:Metals
language:en
Short-container-title:Metals

Author:

Sawlan Zaid¹²^ORCID,Scavino Marco³^ORCID,Tempone Raúl⁴⁵

Affiliation:

1. Department of Mathematics, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

2. Interdisciplinary Research Center for Refining & Advanced Chemicals, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

3. Instituto de Estadística (IESTA), Departamento de Métodos Cuantitativos, FCEA, Universidad de la República, Montevideo 11200, Uruguay

4. Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia

5. Chair of Mathematics for Uncertainty Quantification, RWTH Aachen University, 52072 Aachen, Germany

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.

Publisher

MDPI AG

Link

https://www.mdpi.com/2075-4701/14/5/508/pdf

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