About this role
Geselecteerde taal: EN - Sustainable - Circular and industrial construction - Go to Mobility and logistics - - Efficient drug development - Medical devices - Work health - - - Accurate geo-location with nanosatellites - PERSEUS wind turbine radar interference assessment tool - Military use of space - Integrated combat capabilities - - - TNO Traineeship - Talent development programme - Team Polar - Newsroom - Collaboration - Projects on commission - Public-private - TNO Fast Track - TNO Ventures - Innovation centres Geselecteerde taal: EN - Graduation Internship | Damage localization of a vessel using iFEM and deep learning Locatie: Delft Werken op afstand: On-site Opleidingsniveau: Master Uren per week: 32-40 hours/week Vacancy 1093 Graduation Internship | Damage localization of a vessel using iFEM and deep learning Make your mark on our time! Become an intern at TNO! What will be your role? During this graduation internship, you will investigate and develop how structural damage can be localized after an extreme accidental load. You will develop iFEM tooling to reconstruct displacement and stress/strain fields for loading condition and geometry. Developing and validating a Deep Neural Network or other machine learning method to identify the damage locations. You will combine literature research with calculations and numerical analyses, using tools such as Python and finite element software. Your task will include: - Implemented iFEM tool for navy applications be able to reconstruct displacement and stress/strain fields for a loading condition for a given geometry. - Developing Deep Neural Network (DNN) or another machine learning method to identify the damage location. - Validating the developed tooling. - Potentially, identify the limitations of iFEM for SHM considering noise. - Potentially, developing tool to assess remain strength. Through your work, you will contribute to a larger developm...