Machine learning and finite element analysis: An integrated approach for fatigue lifetime prediction of adhesively bonded joints

Since fatigue investigations are expensive and time consuming, models capable of predicting lifetime by leveraging existing experimental data are desirable. Here, this task is accomplished by combining machine learning (ML) and finite element analysis (FEA). The dataset contains 365 points comprising four adhesives with four different joint types. The model is fed with four input parameters: stress ratio and stress amplitude (functions of the...