BAE data science scheme to accelerate combat air system development

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<p><figcaption class=virtual booth attendant (Image: BAE)

BAE Systems has partnered with the University of Manchester to accelerate the design and development of a new jet aircraft through the use of data science.

To achieve the UK government’s Combat Air Strategy, Team Tempest partners are leveraging new and innovative digital technologies to make the program faster and more efficient, as developing a new fast jet aircraft is a long and complex process. expensive.

The five-year Data Science Accelerator project between BAE Systems and the University of Manchester aims to combat this.

Andrew Gordon, digital and artificial intelligence group leader at BAE Systems Air, said: “There is a wealth of data being captured from some of the incredibly complex systems used in fast jet flight.

“Working in partnership allows both parties to share our experience and knowledge in exploring the captured data.

“The accelerator takes data and helps us formulate simulations and prototypes faster and more cost-effectively than with a siled approach.”

Professor Hujun Yin, Accelerator Academic Lead at the University of Manchester, added: “Data Science Accelerator takes our collaboration with BAE Systems to another level.

“Projects under the Accelerator; from seminars to workshops and sprints to PhDs, they not only provide snapshots of relevant research developments in Manchester, but also offer opportunities for academics to further their research to address the challenges facing BAE Systems and into applications of analysis engineering. data and artificial intelligence techniques.

Aerodynamic testing, such as the use of data from wind tunnel tests, is used to quickly produce different test models and reduce the time it would take to go through the development and design process to save time and money.

Other projects the scheme is exploring include a multi-modal data analysis program that involves developing algorithms that will help aircraft radar with real-time image and object recognition.

It also finds ways to use the data to determine pilot workload and adjust systems in real time, and how to potentially replace sensors with virtual sensors.

Andrew added: “Working in a more dynamic and agile way is essential if we are to produce innovative, smart technology products that our customers want and need for the future.

“We believe that working collaboratively with world-leading academics is critical to the advancement of aerospace technology and I am confident that further collaborations as we move forward will have benefits for all involved, including our customers in the future.”

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