Kufoin, E. and Susmel, L. orcid.org/0000-0001-7753-9176 (2024) Quantitative review of probabilistic approaches to fatigue design in the medium cycle fatigue regime. Probabilistic Engineering Mechanics, 75. 103589. ISSN 0266-8920
Abstract
To quantify the fatigue behaviour of materials, a Wöhler diagram is required. The state of the art shows that, over the years, numerous approaches suitable for determining Wöhler curves have been devised and validated through large fatigue data sets. The variation in experimental fatigue data elicits the use of statistics for analysis and design purposes. By focusing on the medium-cycle fatigue regime (i.e., failures in the range 103÷107 cycles to failure), this paper reviews relevant statistical approaches, particularly the methods suggested by the American Society for Testing Materials (ASTM) as well as the International Institute of Welding (IIW) and the so-called Linear Regression Method (LRM). Their responses were assessed on virtual data sets tailored to satisfy specific statistical requirements as well as experimental fatigue data sets from the literature. While the scatter bands at two times or less of the spread are similar for all approaches, the ASTM approach is seen to be the most conservative.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Medium cycle fatigue; Scatter band; Probability of survival; Regression analyses; Stress levels; Fatigue design |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council 2574292 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 28 Feb 2024 13:13 |
Last Modified: | 30 Aug 2024 13:30 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.probengmech.2024.103589 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209423 |