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Digital twins help engineers to run accurate simulations and optimize the aircraft shape and design for maximum efficiency.

Aerodynamics engineers can identify high drag and turbulence areas in the simulations, make precise adjustments to mitigate drag, optimize wing shape, and improve airflow control. This reduces fuel consumption, lowers emissions, and promotes sustainable aircraft designs.

This is important because aerodynamics plays a vital role in the fuel efficiency and performance of aircraft.

Manufacturers of aviation components have been leading proponents of cutting edge Digital Twin technology in applying Digital Twins to aid their production.

Through creating a Digital Twin, the engineer does not need to rely so heavily on probability and can instead turn to virtual models.

For example, take aircraft engines. To ensure the Digital Twin is accurate, sensors are installed on the physical engine to collect data which is fed back into the Twin in real time. What this does is allow a Digital Twin to function in a virtual world. The Digital Twin operates in the virtual world as the physical engine would on-wing.

This data can then be used to simulate a variety of circumstances which you would not wish to replicate on-board, enabling insight into the engine that would not previously have been available.

Digital twin technology also has been used to train AI to fly autonomous aircraft. AI pilots can get thousands of hours of flight time on a digital simulation in a fraction of that time and learn in days than what it takes, a human pilot, months to experience.

At Boeing digital twins are used to design aircraft. Simulations are run that predict the performance of various aircraft components over the lifecycle. As a result, Boeing engineers can predict when components are expected to fail. According to the company they have achieved a 40% improvement rate in the first-time quality of parts by using a digital twin.

Another use case being explored for Boeing aircraft is using a digital twin to achieve a perfect cargo load balance. For example, a Boeing 737-800 has a maximum cargo load of 80,000 kilograms but many planes fly with less cargo as weight figures are calculated manually. By using IoT sensors on a digital twin, a precise and yet safe cargo load can be determined thereby increasing cargo revenue per flight.

Want to learn more? Tonex offers Digital Twin Training for Aviation Industry, a 2-day course where participants learn the principles of Digital Twins technology and how it relates to integration of Digital Engineering, modeling and simulations, AI/ML, 3D and integration for service and product-related data and systems.

Learn about Digital Twins for managing aircrafts, airports, communications weather issues, natural disasters and other key functions.

Additionally learn about managing aviation infrastructure, assets, people and procedures.

For more information, questions, comments, contact us.

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