hypersonic speed
NASA's pursuit of commercial hypersonic flight was just given an AI-powered boost
One-hour flights anywhere may be some way off yet, but artificial intelligence could play a massive part in speeding up the development of hypersonic airliners. U.S.-based Argonne National Laboratory announced a partnership with NASA to boost hypersonic flight research and make vastly shorter travel times a reality with the help of AI-enhanced computer simulations, a press statement reveals. Hypersonic flight is achieved at a speed of Mach 5, or five times the speed of sound at sea level -- sound travels differently at different altitudes and on different planets. Argonne will bring its supercomputing capacity to the table to help NASA develop its hypersonic testing systems, including experimental aircraft such as its X-43A scramjet-powered aircraft, built as part of its Hyper-X program. The company uses computer fluid dynamics (CDF) to model and predict how an aircraft will react to the forces around it at hypersonic speeds.
Boosting US Fighter Jets - NASA Research Applies Artificial Intelligence To Hypersonic Engine Simulations
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.