Dynamic Digital Twins for Next Generation Mechanical Testing & Control

数字孪生是模型和数据的最佳组合，用于创建真实的系统的虚拟副本。该项目的目的是开发更先进的振动测试技术-例如使用数字孪生模型测试汽车或风力涡轮机，该模型可以建模和预测振动行为。这将做两件事：（1）提高操作效率，以及（2）增加资产的寿命，从而提高其寿命期间的成本效益。该项目由西门子数字工业软件公司赞助，该公司几十年来一直处于工程测试和分析的前沿，因此非常适合与谢菲尔德的学术团队合作支持学生。基于物理的模型将使用FEA软件。基于数据的模型将基于机器学习技术。

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.