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METHODS article
Front. Built Environ.
Sec. Construction Materials
Volume 10 - 2024 |
doi: 10.3389/fbuil.2024.1403245
This article is part of the Research Topic Advancements and Developments of Ultra-High-Performance Concrete (UHPC) and UHPC Structures View all articles
Analytical method of incorporating failure probability to predict the fatigue life of ultra-high-performance concrete (UHPC)
Provisionally accepted- 1 Guangzhou Guangjian Construction Engineering Testing Center Co. Ltd., Guangzhou, China
- 2 Guangzhou University, Guangzhou, China
This study predicted the fatigue life (N) of UHPC incorporated with different volume fractions (V f =0.0%, 0.5%, 1.0%, 1.5% and 2.0%) of steel fiber under flexural cyclic loading at various stress levels (S). The Weibull distribution, a two-parameter model, was utilized to estimate the distribution of fatigue life in UHPC. Subsequently, three methods were employed to calculate the parameters: the graphical method, the method of moments, and the method of maximum likelihood. The averaged values of these parameters were then obtained to enhance the accuracy of the estimation. The results are presented in the form of S-N diagrams, which depict the quantitative relationship between stress (S) and fatigue life (N). This relationship was determined using the Wohler equation, the modified Wohler equation, and the power equation. By employing these equations, the flexural fatigue strength of UHPC can be accurately predicted. Subsequently, the fatigue failure probability (Pf) was incorporated to enhance the reliability of the S-N quantitative relation. The fatigue testing results were presented in the form of S-N-Pf curves, which comprehensively reflect the relationship between stress, fatigue life, and failure probability. Furthermore, the mathematical relation of the S-N-Pf curves was derived to predict the fatigue life of UHPC with a given failure probability, providing a more comprehensive and accurate assessment of its fatigue behavior.
Keywords: Fatigue life, UHPC, Weibull distribution, Probability failure, Fatigue failure probability
Received: 19 Mar 2024; Accepted: 28 Jun 2024.
Copyright: © 2024 Luo, Yang, Niu, Cheng and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yanfei Niu, Guangzhou University, Guangzhou, China
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