About the course

The progress in key-technologies such as Artificial Intelligence and Internet of Things opens new horizons for developing the lightweight structures of the future, where the structures will be able to perform self-diagnostic checks of their integrity, self-estimate their lifespan and communicate with each other valuable information.

This course aims to provide the fundamental knowledge for enabling these key-technologies to transform conventional structures to cyber-physical assets. The lectures will focus on the application of machine learning for design and failure analysis of lightweight structures, AI-based structural health monitoring, diagnostics and prognostics strategies, state awareness capabilities and digital twins.

For whom

This course is aimed for young researchers (PhD’s and PostDoc’s) who want to become independent scientists developing their research in the field of design and failure analysis of lightweight structures using machine learning, structural health monitoring, diagnostics and prognostics and state awareness. The attendants are expected to:    

• have strong knowledge of mechanics of materials (preferably FRP materials)
• be able to apply theory of probability and statistics
• understand the fundamentals of the finite element method
• be familiar with machine learning techniques

During the course, the attendants should expect interactive lectures consisting of classroom activities and concept exercises. A special ‘meet-your-lecture’ session will take place where the attendants will consult the lecturers about their research topics. 

Scholarships

We will provide 3 scholarships to 3 applicants and cover their registration fees. The attendants are welcome to submit their CVs and a motivation letter to Dr. Dimitrios Zarouchas (d.zarouchas@tudelft.nl), addressing the relevance of their research to the content of the course. A committee will assess their applications.

All attendants will receive a certificate of attendance.