Digital copies of people, cities and crises: how scientists are modeling the future

Technology from space: how a digital twin saved Apollo 13

"Houston, we have a problem." Many are familiar with this

the famous phrase, but not everyone knows that the problem, which was reported by the crew of the NASA lunar mission "Apollo 13", helped to solve the prototype digital twin.

The first two days of the Apollo 13 flight have passedcalmly, except for a couple of small surprises, the space agency said. Operator on duty, Joe Kerwin, even said, "We're going to die of boredom here." But this was the last time anyone mentioned boredom.

A few minutes after the communication sessionan oxygen cylinder exploded. Around that moment, the famous phrase sounded: the crew reported the problems to colleagues from NASA. Astronauts saw gas from an oxygen cylinder being thrown into space at high speed. The sensors later showed the loss of two of the three fuel cells. The problems of the mission did not end there, they decided to abandon the landing on the moon. The main task of the engineers who remained on Earth was to urgently figure out how to save the crew, which is located at a distance of more than 320 thousand km from them.

Any wrong decision could lead toirreparable consequences, so it was necessary to act for sure. NASA specialists had 15 simulators at their disposal, which were used to train astronauts and dispatchers, to work out a variety of scenarios, including failures. NASA Flight Director Gene Krantz said one of the most challenging technologies in the entire space program was simulations. All that was real during the training was the crew, cockpit and control panels. Everything else, he noted, was virtual, created by "a bunch of computers, a lot of formulas and skilled people."

To return the crew to Earth centermanagement needed to figure out how to operate a seriously damaged ship in a configuration that was very different from the one for which the calculations were originally carried out. The team had to find new ways to save energy, oxygen and water, figure out how to restart the command module, which is not designed to shutdown in space.

The simulator itself, even in conjunction withall computer systems cannot be called a full-fledged digital twin. But the way the NASA team works can be compared to how doubles work: with the help of simulators, engineers simulated various scenarios that helped them choose the right strategy to get the crew back. Experts list factors why the system that NASA used to rescue the Apollo 13 crew could be considered a prototype digital twin.

  • Digital twins are most useful when linkedwith physical objects inaccessible to direct human influence. They require constant feedback from the physical object to update information and make decisions. In Apollo 13, this role was played by communications;
  • The digital twin must be flexible enoughto react to changes in its associated physical object. NASA reconfigured the simulators in a matter of hours to recreate a configuration that was not envisaged in the design;
  • The Apollo 13 mission did not have a digital twin:the space agency used 15 different simulators to render different details. Modern digital twins also consist of many interacting models.

NASA is now using digital twins todevelopment of recommendations, road maps and new generation ships. “The ultimate goal of the digital twin is to build, test and build equipment in a virtual environment. It is only when we get what meets our requirements that we create it physically. At the same time, we need the object to be connected to the digital twin through sensors and that the digital twin contains all the information about the object, ”explains NASA employee John Vickers.

Where on Earth can digital twins be used?

Design digital twins helptry out more scenarios in advance - on a virtual model, not on a physical object. With the help of twins, you can improve the energy efficiency of a building, optimize the impact on the climate, and obtain information about the loads on the object and failures. And it doesn't matter what kind of object we are talking about - a machine tool, an airplane or a building. Unlike classic simulators, digital twins use real-time data. Moreover, the simulator studies one process, and the twin can run a different number of simulations for calculations.

Digital twin technology, for exampleuses Siemens. The company relies on them to help design gas turbines, organize factories or new buildings, such as at its headquarters in Switzerland. The technology helped create the Solo three-wheeled electric vehicle from Canadian startup Electra Meccanica. Engineers pre-tested and optimized all elements of the car using digital twins.

Where digital twins are used:

  • In industry, digital twins of buildings, technological processes and even individual products are created;
  • Automakers are abandoning crash tests of new car models, replacing them with virtual tests;
  • In the construction industry,BIM technologies. With their help, you can create a model of a new traffic intersection and see how traffic flows are distributed, model a new traffic pattern for pedestrians near the metro and assess how efficient it is and whether it can speed up traffic.

Who has digital twins in Russia

In Russia, the digitization of objects is known formobile laboratories "Yandex" and Google, which travel around cities and take panoramas. Making digital copies of roads and buildings has long made life easier for people by allowing them to route, track traffic congestion, and track repairs along the way. But this is just the tip of the iceberg - doubles can help with more complex navigation.

The development of digital twins in Russia is being carried outRostec and GLONASS. The companies launched a joint project where they collect data from video recorders and combine it with a mathematical model of road infrastructure (the same digital twin) and data from road cameras. Artificial intelligence (AI) analyzes this picture and compares the results with safety standards - the width of the roadway and the number of lanes, the locations of road signs and traffic lights. The program assigns a rating to each section of the road and gives recommendations for its improvement.

AI has already analyzed almost 3,000 km of roads in the Orenburg region and found the most dangerous sections.

What digital tools can do:

  • reduce traffic congestion;
  • track weather and environmental conditions;
  • make better use of resources;
  • simulate the construction of new elements of road infrastructure;
  • calculate options for organizing the movement of unmanned vehicles.

Another Russian project is mobilelaboratories of the company "Digital Roads". They automate and accelerate the process of digitizing the objects of the road network so much that the infrastructure with all the changes will be displayed in real time. The system can fix the location of objects with an accuracy of 10 cm, determine their size and even read what is written on them. The development will provide an objective picture of the state of the infrastructure and will help to keep a thorough record of all objects and changes occurring to them.

A network of mobile laboratories andDVRs can read up to 150 km per day. The system digitizes objects, reports new and temporary objects, and records damage. The platform stores and analyzes the history of their condition, controls advertising signs and even prepares traffic management projects.

Who needs digital twins?

Digital twins are very useful, but not needed forall processes and companies. In some cases, creating a virtual copy of an object will increase its cost, but will not produce the desired result, according to IBM experts.

According to researchers, the use of a doubleneeded for physically large and complex projects such as buildings, bridges, jet turbines, cars and airplanes. The technology will be useful for energy enterprises and industries.

The digital twin market is expanding rapidly andwill continue to grow for at least several more years, experts expect. In 2020, this market was estimated at $ 3.1 billion, and by 2026, according to forecasts of some analysts, it may reach about $ 48.2 billion. Many companies and research institutes have only recently assessed its strength. Now they want to test simulations of large-scale events - global financial crises, wars, or even people.

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