Artifical Intelligence for Science and Government (ASG) is a large, multi-disciplinary project that is being led by The Alan Turing Institute, sponsored by UKRI. I am the lead prinicpal investigator for the digital twins in engineering stream. Specific sub-projects under this theme are enumerated below.
Theoretical foundations of digital twins for complex engineering systems
The SPF theme on Digital Twins for Complex Engineering systems comprises sub-themes focusing on digital twins for civil engineering, the energy and aerospace sectors. Despite the diversity of application areas, there are common challenges faced by each which fall within the remit of: computational statistics and uncertainty quantification, the analysis and approximation of partial differential equations (PDEs), AI and machine learning. These challenges relate to the fundamental question of how to systematically combine data with physics-based models in the creation of digital twins, and how then to correctly incorporate digital twins within a risk-stratified decision-making pipeline.
Digital twins for built environments
Built environments of future cities will need to cope with climate change, and also more intricate energy demands. Avant-gardist systems that present synergies, typically via interactions and feedbacks (e.g. close adaptation of energy supply to peoples’ activities, heat recovery from infrastructure, greening of the city) are natural candidates. However, their evaluation, before implementation, can only be achieved by simulation models that accurately represent these complex, interdependent, time-dependent stochastic feedbacks. New types of measurements are necessary to develop and tune these models.
Digital twins for multiphase flow systems in the oil and gas and fast moving consumer goods industries
Digital twins are replicas of assets and systems that establish a connection between physical and virtual domains. In this programme, we focus on systems in the oil-and-gas, fast-moving-consumer goods manufacturing industries that feature multiphase flows. These flows are central to almost every facet of these industries, which play a major role in the UK and global economy. Within oil-and-gas settings, in spite of decades of research on the complex multiphase flow phenomena that are prevalent in this sector’s applications, a number of significant challenges remain. For instance, three-phase flows comprising oil, water, and air, are exceedingly complex and feature poorly understood dynamics, phase formation and transitions.
Digital twins in aeronautics
The past decade has seen great strides within aeronautics. There has been a sustained effort towards electric propulsion, the deployment of more fuel-efficient aircrafts for commercial travel, and not to mention the new demand for urban aerial taxis—leading to their preliminary development. Across all these scales—large commercial aircrafts, medium sized jets and smaller vertical take-off and landing (VTOL) vehicles—safety, reliability, and efficiency continue to remain paramount; this is especially important given the recent of string of aviation incidences involving fatalities. To ensure both existing machinery and new aviation concepts comply to stringent standards, there is a strong need for more physically representative digital twins of aircraft systems.
Digital twins in infrastructure and construction
The past decade has seen great advances in the development and deployment of sensing technologies for new build, existing and heritage infrastructure. The ability to produce data at multiple scales ranging from optical strain sensors, laser based geometric measurement of whole structures, to satellite based scanning of interactions of structures and geotechnical phenomena is transforming the way in which construction of assets is conducted and how they are operated and managed throughout their lifetime.