Digital Twins of Lubricated Systems and their Evolution

这个学生的目标是为润滑系统开发灵活的预测模型，以描述润滑接触内部的演变。这些模型将使研究时间变化的摩擦学系统以及整合跨尺度的实验和计算技术成为可能。这种集成将使我们能够了解驱动润滑系统摩擦和磨损的潜在过程，并预测其随时间的性能。该预测可用于帮助开发生物衍生和长寿命润滑油，以及改进电动汽车的润滑系统。

This studentship will aim for the development of flexible, predictive models for lubricated systems that can describe the evolution inside lubricated contacts. These models will enable the study of temporally changing tribological systems as well as integrating experimental and computational techniques across the scales. This integration will enable us to understand the underlying processes that drive friction and wear in lubricated systems and predict their performance over time. The prediction can be used to aid the development of bio-derived and longer life lubricants as well as improving the lubrication system in electric vehicles.