What is a Digital Twin and how is it used in engineering?

A DCE digital twin is a digital representation of some physical engineering system - such as a wind turbine, rail network, or an entire city. An adaptive connection between the digital twin and its physical counterpart allows the virtual representation to update in real-time, throughout the lifecycle of the monitored system. The associated techniques will typically correspond to the fusion of conventional engineering practice with machine learning, data science, and statistics - in response to the increasing prevalence of data. By utilising simulation, digital twins allow testing on the digital before the physical, such that our interactions with engineering systems become more efficient, economic, and sustainable. A digital twin should enable real-time decision making and actional insight, supporting the move towards smarter engineering systems and infrastructure.

This collection brings together articles that explore the use of digital twins from the Data-Centric Engineering, Data & Policy and Environmental Data Science open access journals, in addition a talk focused on digital twins from the DCE Webinar series. Authors interested in submitting their work on digital twins should consult the Instructions for Authors of these journals.

DCE Webinars

Watch the following talks on digital twins from our webinar series: 

• Real-time digital twins: unifying bias-aware data assimilation and machine learning with Andrea Nóvoa(Imperial College London)
• Digital twins for underground infrastructure with Jelena Ninić (University of Birmingham) and Brian Sheil (University of Cambridge)
• Digital twins for mechanics and medicine with Stephane Bordas (University of Luxembourg)
• Does a digital twin have a digital twin? with Julie McCann (Imperial College London)