What’s a digital twin?
A digital twin is a computer model that we can use to simulate something in the real world – be that a vehicle, a building, or an entire city. Analysing the model’s output tells us about the behaviour of the real thing, which can inform the real-world decisions we make about it.
In this case, we’re modelling a 3D printed bridge. We have created a digital representation of the bridge’s structure, and sensors on the bridge feed into our model to tell us how the material is behaving, and how the bridge is being used. The work involved researchers from the Turing’s data-centric engineering programme, alongside a global team of collaborators from MX3D, Arup, Autodesk, FORCE Technology and the University of Twente.
Tell us about the ‘real’ bridge in Amsterdam
It’s a 12-metre-long footbridge over the Oudezijds Achterburgwal canal in central Amsterdam, created by MX3D using robotic arms that deposit the steel layer-by-layer. This technique is completely automated and it gives greater precision and uses less steel than conventional methods. It also gives engineers more control over the bridge’s shape, so that they can create features like these swooping curves.
What sensors do you have on the bridge?
We’ve got around 100 sensors in total, measuring the bridge’s load and how the bridge vibrates, bends and tilts as people cross it. We have sensors monitoring the temperature and humidity, as these will affect how the steel behaves, and we also have video cameras to record how people are using the bridge.
How does the data feed into your model?
The data from the sensors is wired to a server in the basement of a nearby building, where it’s uploaded to remote servers in the cloud. The team has developed software that uses this data to continuously update our computer model so that it’s as close as possible to the real thing. We’ll use the model to analyse how the bridge is behaving, and look for any differences with our initial calculations. This is the largest 3D printed metal structure in the world. It’s a new way of building, so we’re interested in finding out if the steel performs as we expect. We have lots of lab data, but this will be the first real-world test. Once we understand the material, we can look for new ways of building with it.
Do the pedestrians know that it’s a smart bridge?
Yes, there’s a sign on the bridge explaining that it’s a research project and that we are collecting data. The data is anonymised: there are no privacy issues with the video recordings because the software automatically converts the pedestrians’ images into stick figures before any researchers access the recordings.
What will you do with the video recordings?
We plan to analyse them to find out things like the number of people using the bridge and how long they stay there. Will the bridge become a hub in the city where people hang out? Will tourists stop by and take selfies?
This all fits into the bigger picture of the smart city. If we have data on how citizens are using different areas and structures, the authorities can better plan the surrounding environment. We know that pedestrian areas are a good place to put shops and cafés, for instance, because the businesses will benefit from the extra footfall. Data-collecting structures like this bridge will help planners to get a better idea of how they should be laying out their cities.
What’s the future of this technology?
Cities of the future could have an interconnected system of digital twins, where we can simulate how changes to one digital twin – such as a representation of the rail network or the water infrastructure – cascade through the system. This could help authorities to predict problems before they even happen.
Collecting more data about our cities can also help us to push towards making them greener. If we have data on how carbon dioxide levels in the city decrease when we plant trees, or on how the local economy is benefitting from pedestrian areas, it helps make the case for adding more trees or pedestrian areas. Ultimately, the goal is to make our cities happier places to live, and data science has a crucial role to play.
Top image: Thea van den Heuvel
