Advances in concrete construction

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Degradation reliability modeling of plain concrete for pavement under flexural fatigue loading

  • Jia, Yanshun (School of Transportation, Southeast University) ;
  • Liu, Guoqiang (School of Transportation, Southeast University) ;
  • Yang, Yunmeng (Richangsheng Design & Research Institute of Building New Materials Co., Ltd.) ;
  • Gao, Ying (School of Transportation, Southeast University) ;
  • Yang, Tao (School of Transportation, Southeast University) ;
  • Tang, Fanlong (School of Transportation, Southeast University)
  • Received : 2019.09.29
  • Accepted : 2020.04.30
  • Published : 2020.05.25
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Abstract

This study aims to establish a new methodological framework for the evaluation of the evolution of the reliability of plain concrete for pavement vs number of cycles under flexural fatigue loading. According to the framework, a new method calculating the reliability was proposed through probability simulation in order to describe a random accumulation of fatigue damage, which combines reliability theory, one-to-one probability density functions transformation technique, cumulative fatigue damage theory and Weibull distribution theory. Then the statistical analysis of flexural fatigue performance of cement concrete tested was carried out utilizing Weibull distribution. Ultimately, the reliability for the tested cement concrete was obtained by the proposed method. Results indicate that the stochastic evolution behavior of concrete materials under fatigue loading can be captured by the established framework. The flexural fatigue life data of concrete at different stress levels is well described utilizing the two-parameter Weibull distribution. The evolution of reliability for concrete materials tested in this study develops by three stages and may corresponds to develop stages of cracking. The proposed method may also be available for the analysis of degradation behaviors under non-fatigue conditions.

Keywords

Acknowledgement

This research was sponsored by the National Natural Science Foundation of China (No. 51878168) and Postgraduate Research & Practice Innovation Program of Jiangsu Province (Nos. KYCX18_0141 and KYCX18_0142). This support is gratefully acknowledged.

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