Abstract
Ocean structures are subjected to random environmental loads during their service life. Under the action of random loads, fatigue crack growth within pipeline steel exhibits transient behaviors such as retardation or acceleration. This poses significant challenges in predicting the fatigue life of ocean structures under random loadings. To establish a predictive model for fatigue crack growth in X80 pipeline steel under random loadings, this study first conducts fatigue crack growth experiments under constant amplitude and random loading conditions. Then, based on deep learning methods and the fracture yield zone theory, a phenomenological model is developed to predict fatigue crack growth in X80 pipeline steel under random loading conditions. The results show that under random loading conditions, the fatigue crack growth curve of X80 pipeline steel maintains a relatively clear logarithmic-linear feature during the stable crack growth stage. However, due to the continuous variation of stress ratio with loading sequence, the fatigue crack growth curve exhibits strong fluctuation characteristics; The phenomenological model established in this study for predicting fatigue crack growth under random loading conditions can relatively accurately reflect the overall trend of fatigue crack growth under random loadings, with a maximum prediction error of less than 10%.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
