Research CollaborationWe present an exciting research project: AI-Driven Temperature and Thermal Mechanical Fatigue Forecasting. This thesis offers a unique opportunity to validate AI-based temperature field predictions and thermal mechanical fatigue (TMF) life predictions for head valve seat bridges.ResponsibilitiesAnalyze existing simulation and test data from AVL databasesValidate AI-driven temperature field predictions compared to virtual simulationsValidate AI-driven TMF predictions against thermal shock tests and virtual simulationsDetermine key parameters influencing temperature and TMF life predictionDevelop and train an AI model to predict temperature and TMF of valve seat bridgesVerify simulation accuracy by identifying and validating key parameters influencing thermal fatigue lifeYour QualificationsBachelor of Science in disciplines similar to Mechanical Engineering, Physics or a related fieldInterest in Internal Combustion Engine (ICE) technology and conducting mechanical analysis using numerical modeling and simulation techniquesFamiliarity with structural mechanics principles and 3D Finite Element Analysis (FEA) simulation methods is beneficialStrong interest in AI methodologies and programming, particularly with Python, for developing and automating various aspects of the projectOpportunitiesYou will have the chance to write your thesis independently and receive professional guidance and support from our experienced experts. You will also have the opportunity to exchange ideas with experts in the field and benefit from their expertise.