Dynamic Digital Twins for Next Generation Mechanical Testing & Control

A digital twin is an optimal combination of models and data used to create a virtual duplicate of a real system. The aim of this project is to develop more advanced vibration testing techniques - for example for testing automotive vehicles, or wind turbines using a digital twin which can model and predict the vibration behaviour. This will do two things: (1) improve efficiency of operation, and (2) increase the longevity of the asset, thereby improving cost effectiveness over its lifetime. The project is sponsored by Siemens Digital Industries Software, a company that has been at the cutting edge of engineering testing and analysis for several decades, and consequently are ideally placed to support the student in partnership with the academic team from Sheffield. The physics-based models will use FEA software. The data-based models will be based on machine learning techniques.