A new probability model of residual strength of material based on interference theory. (January 2019)

• Record Type: Journal Article
• Authors: Gao, Jianxiong; An, Zongwen
• Is Part Of: International journal of fatigue. Volume 118(2019)
• Page Start: 202
• Page End: 208
• Publication Date: 2019-01
• Subjects: Residual strength -- Degradation rule -- Fatigue life -- Reliability -- Weibull distribution; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2018.09.015
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: The disadvantages of existing residual strength models are analyzed and discussed. A probability model of residual strength is proposed based on interference theory. The model is derived from theoretical deduction rather than subjective experiences. Establishing the model only requires fatigue life data of material. Abstract: The strength degradation rule of material under constant amplitude cyclic loading is critical to fatigue life prediction and reliability assessment of material. In this study, the disadvantages of the existing phenomenological residual strength models are analyzed and discussed, and a new probability model of residual strength of material is proposed based on interference theory. Firstly, the loading times—fatigue life (LT—FL) interference model and the cyclic stress—residual strength (CS—RS) interference model are respectively established based on Weibull distribution. Then, a new probability model of residual strength is derived based on the equivalence between LT—FL and CS—RS interference models. Finally, the fatigue test data of unidirectional carbon/epoxy composites are used to verify the validity of the proposed model. Compared with the existing phenomenological residual strength models, the proposed model is derived from theoretical deduction and it can be easily established only through fatigue life data of material, while the existing phenomenological residual strength models are usually derived from subjective experiences and the establishment of these models generally requires a variety of experimental data of material.