Energy-based time derivative damage accumulation model under uniaxial and multiaxial random loadings

• Published in: arXiv.org
• Main Authors: Shih-Chuan Tien, Haoyang Wei, Chen, Jie, Liu, Yongming
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 03.06.2021
• Subjects: Crack propagation; Damage accumulation; Damage assessment; Equivalence; Fatigue failure; Fatigue life; Fracture mechanics; Growth models; High cycle fatigue; Life prediction; Load history; Low cycle fatigue; Time domain analysis
• ISSN: 2331-8422

A new fatigue life prediction method using the energy-based approach under uniaxial and multiaxial random loadings is proposed in this paper. One unique characteristic of the proposed method is that it uses time-derivative damage accumulation model compared to the classical cycle-based damage accumulation model. Thus, damage under arbitrary random loading can be directly obtained using time-domain integration without cycle counting (e.g., rain-flow cycle counting method in classical fatigue analysis). First, a brief review of existing models is given focusing on their applicability to uniaxial/multiaxial, constant/random, and high cycle fatigue/low cycle fatigue loading regimes. It is observed that most existing models are only applicable to certain loading conditions and many of them are not applicable/validated under random loadings. Next, a time-derivative damage accumulation model under uniaxial random loading is proposed. The proposed damage function is inspired by a time-domain fatigue crack growth model. The fatigue life is obtained by integrating the damage function following random energy loading histories. Following this, an equivalent energy concept for general multiaxial loading conditions is used to convert the random multiaxial loading to an equivalent random uniaxial loading, where the time-derivative damage model can be used. Finally, the proposed model is validated with extensive experimental data from open literature and in-house testing data under various constant and random spectrum loadings. Conclusions and future work are suggested based on the findings from this study.