
Thesis - AI-Based Temperature and Thermal Mechanical Fatigue Prediction
- Graz, Steiermark
- Unbefristet
- Vollzeit
- Review and analyze existing simulation and test data from AVL iCA FE and powertrain databases
- Validate AI-based temperature field predictions compared to virtual simulations
- Validate AI-based TMF predictions against thermal shock tests and virtual simulations
- Identify key parameters (e.g., temperature, geometry, coolant flow) influencing temperature and TMF life prediction
- Develop and train an AI model to predict temperature and TMF of valve seat bridges
- Confirm simulation accuracy by identifying and validating key parameters influencing thermal fatigue life
- Bachelor of Science in domains similar to Mechanical Engineering, Physics or a related field
- Interest in Internal Combustion Engine (ICE) technology and conducting mechanical analysis using numerical modeling and simulation techniques
- Familiarity with structural mechanics principles and 3D Finite Element Analysis (FEA) simulation methods is appreciated
- Strong interest in AI methodologies and programming, particularly with Python, for developing and automating various aspects of the project
- You can write your thesis independently and receive professional guidance and support from our experienced employees.
- You will have the opportunity to exchange ideas with experts in the company and benefit from their expertise.
- Take the opportunity to immerse yourself in the world of AVL and embed your theoretical knowledge in a practical environment.