Digital twins for improved dynamic design

Lead Research Organisation: University of Sheffield
Department Name: Mechanical Engineering


The aim of this proposal is to create a robustly-validated virtual prediction tool called a "digital twin". This is urgently needed to overcome limitations in current industrial practice that increasingly rely on large computer-based models to make critical design and operational decisions for systems such as wind farms, nuclear power stations and aircraft. The digital twin is much more than just a numerical model: It is a "virtualised" proxy version of the physical system built from a fusion of data with models of differing fidelity, using novel techniques in uncertainty analysis, model reduction, and experimental validation. In this project, we will deliver the transformative new science required to generate digital twin technology for key sectors of UK industry: specifically power generation, automotive and aerospace. The results from the project will empower industry with the ability to create digital twins as predictive tools for real-world problems that (i) radically improve design methodology leading to significant cost savings, and (ii) transform uncertainty management of key industrial assets, enabling a step change reduction in the associated operation and management costs. Ultimately, we envisage that the scientific advancements proposed here will revolutionise the engineering design-to-decommission cycle for a wide range of engineering applications of value to the UK.

Planned Impact

This project will have economic impact in the offshore wind, nuclear power, aerospace and automotive industries. The development of new digital twin technology will enable companies working in these sectors to design and operate their products and assets with lower design and operational costs. There may also be benefits in terms of extending operational life. In terms of societal impact, this will contribute to lower energy costs, reduced CO2 emissions, and employment security in the UK. The development of new knowledge, both in the academic domain and translated to industry will happen in parallel with the training and development of a cohort of expert early career researchers. These expert researchers are a key resource for the UK skills base, and they will contribute to the ongoing competiveness of the industrial sectors mentioned above.


10 25 50
Description In the first half of the project, the activities have been deliberately weighted towards developing the new science required to achieve the project objectives. Full details are given in the mid-term report, but the main scientific highlights so far are:
A1. A logic-based framework for the analysis and synthesis of digital twin
A2. Domain adaption and multi-task learning for digital twin applications
A3. Development of new uncertainty propagation techniques in dynamic sub-structuring
A4. Improved robustness of nonlinear parameter identification using control-based continuation

As the project moves into its second half, there will be an increased emphasis on impact. In the mid-term report we highlighted the following achievements so far:
I1. An "observational digital twin" for an aircraft ground-steering system
I2. Work with Airbus on the Semi Aeroelastic Hinge (Albatross-one)
I3. Code libraries & Puffin software for intrusive uncertainty quantification (UQ) objects and operations
I4. Digital Twin Operational Platform (DTOP) for the 3-storey structure (now Use Case U0)

In addition to the above points, fundamental research work has also been carried out in the key areas relating to verification & validation, uncertainty analysis, control, jointing, design and hybrid testing.
Exploitation Route The outcomes of this award are being used by the project industry partners, and we are in discussion with other potential users of the results from the project. In particular we are planning to further develop the open source software release on Github during 2021
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Energy

Description Team members at Swansea have been collaborating with Airbus on the Semi Aeroelastic Hinge (Albatross-one). The main idea behind this project is the use of folding wingtip devices that increase the aspect ratio and therefore improve the aircraft efficiency & performance. Specifically, the linked PhD student started working on this in January 2019. There are continuing discussions with Dr AC about the comparison of results of the developed model at Swansea with the high-fidelity model at Airbus. There is also the possibility of using physical test data from Airbus. Digital Twin Operational Platform (DTOP): A web-based operational platform has been written for application of the digital twin concept to applications. This platform has been written using the Flask Python programming framework. It includes input from all partners and themes across the consortium. The code uses Flask/Python and Javascript to present real-time information on the web visualisation interface. This user-interface is used to showcase the algorithms developed in each of the Themes. We are now exploring use this platform for industry applications, and have released a early version as an open software project on Github:
First Year Of Impact 2019
Sector Aerospace, Defence and Marine
Impact Types Economic

Description Advice given on the development of the Gemini Principles for digital twins
Geographic Reach National 
Policy Influence Type Participation in a advisory committee
Description Advice on the research landscape for Digital Twins in the UK for the Futures Team at the Government Office for Science (BEIS) & UKRI.
Geographic Reach National 
Policy Influence Type Participation in a advisory committee
Title Real-Time Hybrid Testing of Strut-Braced Wing Under Aerodynamic Loading Using an Electrodynamic Actuator 
Description Dataset for: "Real-Time Hybrid Testing of Strut-Braced Wing Under Aerodynamic Loading Using an Electrodynamic Actuator". Authors: V. Ruffini, C. Szczyglowski, D.A.W. Barton, M. Lowenberg, S.A. Neild Journal: Experimental Techniques. 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
Description Digital Twin Workshop 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Study participants or study members
Results and Impact This workshop was hosted jointly between the University of Sheffield Advanced Manufacturing Research Centre and Faculty of Engineering, and was held in the state-of-the-art AMRC Factory 2050 on the Sheffield Advanced Manufacturing Park. The purpose of the workshop was to bring together leading UK based researchers currently working on topics related to digital twin. The contributions included both application specific, and basic research presentations. The event helped to promote the 'Gemini Principles', the 'National digital twin', and the EPSRC funded `DigiTwin' project.
Year(s) Of Engagement Activity 2019
Description The 3rd Sheffield Workshop on Structural Dynamics 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact Over 200 people attended a 3 day online workshop hosted by Prof Keith Worden (DigiTwin Investigator/Member of Management committee) The main body of the workshop had three distinct themes: physics-informed machine learning, population-based SHM, and digital-twins and their validation. The agenda for the workshop allowed time for question and discussions for all attendees. The workshop also provided an opportunity to showcase updates and research within the DigiTwin project.
Year(s) Of Engagement Activity 2020