Researchers from the National Aeronautics and Space Administration (NASA) have teamed up with the US Department of Energy's Argonne National Laboratory (ANL) to develop artificial intelligence (AI) to enhance the speed of simulations to study the behavior of air surrounding supersonic and hypersonic aircraft engines. Fighter jets such as F-15s regularly exceed Mach 2 – two times the speed of sound – during the flight which is known as supersonic level. On a hypersonic flight which is Mach 5 and beyond, an aircraft flies faster than 3,000 miles per hour. Hypersonic speeds have been made possible since the 1950s by the propulsions systems used for rockets however, engineers and scientists are working on advanced jet engine designs to make the hypersonic flight much less expensive than a rocket launch and more common such as for commercial flight, space exploration, and national defense purposes. The newly published paper by a team of researchers from NASA and ANL details the machine learning techniques to reduce the memory and cost required to conduct computational fluid dynamics (CFD) simulations related to fuel combustion at supersonic and hypersonic speeds.

Argonne National Laboratory and NASA researchers have published a paper on the use of artificial intelligence to speed up simulations of air behavior surrounding supersonic and hypersonic aircraft propulsion systems. The partners trained a neural network to find shortcuts to answers about fuel combustion at environments faster than sound, reducing the memory and cost required to conduct computational fluid dynamics simulations, Argonne said Wednesday. The AI technology is expected to enhance the current process of running massive tables of combustion data through NASA's VULCAN-CFD hypersonic code and accelerate the development of barrier-breaking engines for supersonic and hypersonic aircraft. "Working with NASA gave us the opportunity to integrate our novel developments in a state-of-the-art CFD code, and also to further improve the developments for more efficient design and optimization of hypersonic jets," explained Sinan Demir, an Argonne computational scientist. The research paper was previously presented at the American Institute of Aeronautics and Astronautics SciTech Forum in January.