Abstract：Corrosion fatigue is one of the key failure modes in modern industrial equipments. With the continuous development of new technology, equipments in aerospace, rail transit and offshore are becoming more and more high reliability, long life and intelligence. Therefore, an urgent need is required for predicting corrosion fatigue life accuratly and efficiently. In this paper, the corrosion fatigue damage mechanism and life prediction models for pre-corroded fatigue and corrosion fatigue are summarized and commented systematically. Meanwhile, the prospective research directions are proposed. Firstly, the corrosion fatigue failure mechanism and its characterization methods are briefly summarized involving the evolution of corrosion pit, crack initiation and crack propagation. Secondly, the single crack and multi cracks hypothesis based on traditional fracture mechanics models of pre-corroded fatigue are elaborated. The fatigue life prediction models of pre-corroded simple parts based on damage mechanics are also summarized. Those methods are similar to the conventional fatigue life prediction methods for defective components. Additionally, for corrosion fatigue, the different stages based on fracture mechanics models are reviewed. And several quantifying damage dynamically representive corrosion fatigue damage mechanics models are presented. Thirdly, the more efficient data-driven models of corrosion fatigue are thoroughly analyzed. And the advantages and disadvantages of existing models are generalized. At last, based on the current research status, the possible development directions in the future are prospected. It is necessary to realize the visualization research of pit to crack transition stage and short crack propagation process by means of 3D imaging technology and so as to further improve the existing fracture mechanics models of corrosion fatigue. It is suggested to establish a new multi-scale and multi-stage life prediction model with corresponding failure stage correlation. In addition it is important to point out that the new data-driven physical fusion method is a new development direction to predict corrosion fatigue life.
2023, Vol. 44 
