Understanding geometrical size effect on fatigue life of A588 steel using a machine learning approach
Wenke Yang, Bing-Li Hu, Yan‐Wen Luo, Zhu-Man Song, Guangping Zhang
Abstract
In this paper, both experimental and machine learning results show that the fatigue life of A588 steel specimens with different gauge lengths and widths varies more greatly compared with that of the specimens with different thicknesses as the gauge dimensions are reduced from 15 mm to 1.5 mm. The optimal machine learning algorithm is derived to predict the fatigue life of specimens with a thickness of 1 mm, and the predicted results are verified by the fatigue experiments.
Topics & Concepts
Gauge (firearms)Materials scienceStructural engineeringComposite materialComputer scienceEngineeringMetallurgyFatigue and fracture mechanicsNon-Destructive Testing TechniquesMetallurgy and Material Forming