14.04.2025
Master thesis (m/f/d): Machine Learning based Prediction for Influence Coefficients of Stress Intensity Factors
The aim of this thesis is to improve the accuracy and efficiency of fatigue crack growth estimations by developing a computational model that considers multi-axial loadings for risk and reliability assessments of structural components. The work involves acquiring theoretical knowledge, developing influence coefficient databases, and creating a machine learning model to predict these coefficients for different cracked geometries under multi-axial loadings. We look forward to your application!