Seeing double: Digital twins and net zero
5 July, 2022 RRS Sir David Attenborough
This week (2-8 July) is Net Zero Week in the UK – an initiative to bring attention to the need to reach Net Zero, and the challenges and opportunities there are along the way. In 2019, the UK committed to reduce all greenhouse gas emissions by 2050, and now the EU and many other nations have done the same.
Net zero is different from being ‘carbon neutral’, which can be achieved by offsetting your carbon emissions. Becoming net zero is all about reducing carbon emissions as much as possible by becoming more energy efficient, and only offsetting any remaining emissions that are very difficult to remove.
Reaching net zero, as a country or a business, requires new measures, technology and innovations. Digital twins are an example of this; they can be a powerful tool to drive innovation and efficiency. A digital twin is a virtual model, coupled to a physical thing through data – in our case, the RRS Sir David Attenborough coupled by its observations made on ship.
The term ‘digital twin’ was coined by NASA in 2010, although the concept itself is much older. In fact, NASA pioneered the use of this technology in the 1970s, during the Apollo 13 mission. Initially, digital twins were just complex models, but with the advent of Artificial Intelligence (AI) these digital twins can constantly learn from a diverse range of datasets. For example, in Formula 1 racing McLaren and Red Bull use digital twins of their cars, learning from how the car responds on the track before predicting what will happen with changing conditions.
So, how does it work? The object being modelled, whether it’s a building or a car or a ship, is fitted with various sensors which measure a range of different observations. The data collected by these sensors are then used by model to learn how it responded to the conditions at different moments in time. But digital twins aren’t just useful because they help us to understand how something is performing – they can help us understand how it could perform in the future. We can use the model to run simulations and identify where we can improve the object’s performance.
One of the main benefits of digital twins is improving efficiency – and this is exactly how we’re using the technology at BAS!
Our project, AI and Digital Twinning for Decarbonisation, is working to reduce carbon emissions from Britain’s new polar ship RRS Sir David Attenborough. Scientists are working to create a Digital Twin used in ship navigation, which will be able to recommend the fastest and most energy efficient routes for the ship’s journey. This system is like the in-car navigation system that many of us use, but with the added complexity that the ocean around Antarctica contains no roads and has ever changing conditions that affect the routes between destinations
The project involves building an initial automated decision-making tool to optimise route planning for carbon efficiency. As more data is collected the Digital Twin will be reinforced with how the real ship responded to different conditions, further maximising carbon efficiency.
The ship’s digital twin will make use of all the different data available onboard, as well as varying environmental conditions observed from satellite data and models such as: variations in sea ice concentrations, changing weather conditions, and hazards such as icebergs. This toolkit will allow ship’s Captain to run scenarios and look at the proposed routes for different conditions, using their vast knowledge and experience to decide the best option for sailing around Antarctica!