Digital twins in F1 and the built environment

People are talking a lot about digital twins these days. A digital twin is a virtual representation of something real, using data and algorithms in place of materials and connections.

If you watch the British Grand Prix this year, spare a thought for the digital twins that sit behind the sport.

Teams use simulators to evaluate the performance and reliability of new parts. The top teams are manufacturing 3,000 new components every week in pursuit of ever improving lap times.

Mathematical models of the powertrain and tyres run at the track and tell the race engineers about the remaining life and performance left in these critical components.

Analytics process the lap times of all of the cars throughout the race weekend to lead the teams towards optimum set-up and pit strategies. And so on.

Huge real-time data collection: data collected every 0.001 seconds

The digital twins are validated with real data and observations.

A race car has over 150 sensors measuring temperatures, pressures, accelerations, forces and shaft speeds.

Data from these sensors are collected every thousandth of a second and transmitted back to the garage in real-time using telemetry.

Each car sends over a billion numbers in a two-hour race. And those digital twins in the garage, which add virtual sensing into the mix, increase the amount of real-time data to about 5 billion numbers.

Digital twins have certainly transformed Formula One. Teams are developing complex cars that are safer, more reliable, and higher performing than could ever have been imagined before digital twins started gaining prominence over a decade ago.

Digital twins can benefit the built environment: better operation, less maintenance

We're beginning to see digital twins emerge in the built environment.

The problem is often messier than racing cars travelling around a prescribed path, but the essential value they deliver remains the same.

The digital twins can promote better understanding of how assets, processes and complex systems behave, or might behave in the future, to local interventions and the environment.

They can help things run better and longer, avoiding sudden and surprising deterioration and harm.

The key is to understand which information is needed, and how often to refresh

It's important to understand what's important to a community or organisation, to identify critical components and interventions, to monitor activity and environment, and to develop and deploy trusted and meaningful digital twins. And then have the belief and courage to act.

The data that feeds the digital twins comes from observations, cameras, sensors and other sources across the built environment.

Many of the data sources are updated far less often than the sensors on a Formula One car, but frequently enough to keep the digital twins fresh and relevant.

Data collection reduces risk and uncertainty

This approach, done well, reduces uncertainty and risk, and establishes context for well-judged and well-timed interventions. This can lead to sustained improvements in the buildings, energy and water infrastructures, transportation and other vital ingredients of everyday life.

It makes sense from economic, environmental and social perspectives.

Frazer-Nash Consultancy works in the defence, energy and transportation sectors. The company exploits science, measurement and mathematics to assure the performance, availability and safety of complex systems.