Probabilistic formulation of Miner's rule and application to structural fatigue

被引:5
|
作者
Cartiaux, Francois-Baptiste [1 ]
Ehrlacher, Alain [2 ]
Legoll, Frederic [2 ,3 ]
Libal, Alex [2 ,4 ]
Reygner, Julien [4 ]
机构
[1] OSMOS Grp, Puteaux La Defense, France
[2] Univ Gustave Eiffel, Ecole Ponts, Navier, CNRS, Marne La Vallee, France
[3] Inria, MATHERIALS Project Team, Paris, France
[4] CERMICS, Ecole Ponts, Marne La Vallee, France
关键词
S-N curves; Miner's rule; Probabilistic formulations; Weibull-Basquin model; Size effects;
D O I
10.1016/j.probengmech.2023.103500
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The standard stress-based approach to fatigue relies on the use of S-N curves, which are obtained by applying cyclic loading of constant amplitude S to identical and standardised specimens until they fail. For some reference probability p, the S-N curve indicates the number of cycles N at which a proportion p of specimens have failed. Based on these curves, Miner's rule is a widely employed method which yields a predicted number of cycles to failure of a specimen subjected to cyclic loading with variable amplitude. The first main contribution of this article is to introduce a probabilistic model for the number of cycles to failure and to show that, under mild assumptions, the deterministic number returned by Miner's rule is the quantile of order p of this random number of cycles to failure, which demonstrates the consistency of our formulation with standard approaches. Our formulation is based on the introduction of the notion of health of a specimen. Explicit formulas are derived in the case of the Weibull-Basquin model. We next turn to the case of a complete mechanical structure: taking into account size effects, and using the weakest link principle, we establish formulas for the survival probability of the structure. We illustrate our results by numerical simulations on a I-steel beam, for which we compute survival probabilities and density of failure point. We also show how to efficiently approximate these quantities using the Laplace method.
引用
收藏
页数:14
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