NASA Funds Four University Teams to Tackle Aviation’s Next Big Challenges

NASA has handed the next generation of aviation researchers a rather ambitious shopping list: make aircraft faster, quieter, safer and easier to certify. Four university teams have now been selected to tackle some of those challenges under NASA’s University Leadership Initiative, with around $30 million in funding supporting their work over the coming years.

The research ranges from propulsion systems intended to push aircraft beyond Mach 4 to artificial intelligence for aircraft avionics, sophisticated tools intended to make aircraft certification less painful, and flight-planning technology designed to stop future urban air taxis from turning cities into giant acoustic laboratories.

The awards are the ninth round of funding under NASA’s University Leadership Initiative, which brings together undergraduate and graduate students, university researchers, industry partners and government agencies. NASA, the Federal Aviation Administration and other organisations provide technical support and guidance.

For NASA, the idea is about more than producing research papers. The initiative is also intended to develop the aerospace workforce that will eventually have to turn today's experimental concepts into tomorrow's aircraft.

The Mach 4 challenge

The University of Minnesota has perhaps the most obviously dramatic assignment. Led by Terrence Meyer, its four-year project will investigate an Adaptive Supersonic Combined Cycle Engine for Next-generation Transportation.

The concept involves an aircraft that uses a conventional turbofan for take-off and subsonic flight, then transitions to a different propulsion system for supersonic operations. That second system would use ramjet technology, allowing the aircraft to operate at speeds of around Mach 4, more than 3,000 mph - The attraction is obvious - A propulsion system that can efficiently operate across a wide range of speeds could potentially overcome one of the biggest problems facing high-speed aviation: an engine that works beautifully in one flight regime may be considerably less impressive in another.

The Minnesota team will therefore be looking at a fuel-flexible system capable of adapting to different phases of flight, with the ultimate goal of making high-supersonic transportation more practical. If successful, it could help revive the dream of routine passenger flights at speeds well beyond those of today's fastest commercial aircraft.

Teaching avionics to learn — Safely

Stanford University has been awarded two separate projects, with one focusing on a subject that is becoming increasingly difficult for aviation regulators and engineers to ignore: artificial intelligence. Led by Somil Bansal, the Safety Across Lifecycle of Learning-Enabled Avionics Systems project will examine how machine-learning technology can be incorporated into aircraft systems responsible for communications, navigation and other electronic functions.

The interesting part is not simply putting AI into an aircraft. Aviation has never been particularly enthusiastic about the philosophy of "let's see what the computer does". Instead, the Stanford team wants to develop what NASA describes as a Safety Data Flywheel, an approach in which safety is continuously reinforced throughout the operational life of an AI-enabled system.

That could become increasingly important as machine-learning systems move from laboratories into operational aircraft. Conventional avionics are generally designed around predictable behaviour. AI systems can introduce a very different set of challenges, particularly when it comes to proving that they will remain safe when confronted with situations that were not anticipated during development.

The research could ultimately help establish a framework for introducing AI-enabled avionics into the national airspace system without asking regulators to simply take a leap of faith.

Making urban air mobility quieter

Stanford's second project tackles another problem that could determine whether urban air mobility succeeds or becomes the aviation industry's latest public-relations headache: noise. Led by Juan Alonso, the project will develop a high-fidelity simulation framework for planning low-noise flight paths for future small aircraft operating over populated areas.

Urban air mobility promises to move passengers and cargo across cities without relying entirely on congested roads. But while the concept looks attractive on a PowerPoint presentation, the sound of hundreds of aircraft flying overhead could produce a rather different public reaction. Stanford's researchers intend to incorporate realistic models of how sound travels through urban environments. The objective is to develop flight trajectories that minimise the exposure of communities to aircraft noise.

In other words, the future urban air taxi may not simply need to know where it is going. It may also need to know which neighbourhoods would prefer that it went somewhere else.

Designing aircraft with uncertainty in mind

Virginia Tech is taking on another perennial aviation problem: aircraft design and certification. Its three-year Certification Driven Aircraft Design Under Uncertainty project, led by Darshan Sarojini, aims to combine advanced computer modelling with the aircraft development process.

The project will bring together model-based systems engineering, multidisciplinary design and optimisation, and high-dimensional uncertainty quantification. That may sound like a recipe for making aircraft development even more complicated. The intention, however, is precisely the opposite. Aircraft development is expensive, and discovering a major problem late in the design process can mean costly redesigns, delays and certification headaches. By accounting for uncertainty much earlier, the Virginia Tech team hopes to produce designs that can be evaluated more quickly and confidently.

The long-term objective is an aircraft development process that is safer, faster and more efficient — with fewer unpleasant surprises waiting near the end of the programme.

Building aviation's next generation

NASA's University Leadership Initiative has been running for more than a decade, and these latest awards demonstrate how broad the agency's definition of "future aviation" has become.

It is no longer simply about building a faster aircraft. The next generation of aviation will require propulsion systems capable of radically different speeds, avionics that can safely incorporate artificial intelligence, aircraft that can operate over cities without annoying everyone underneath them, and design processes capable of dealing with increasingly complex engineering problems.

The common thread is that none of these challenges can be solved by one organisation working alone. By putting universities, students, industry and government researchers around the same table, NASA is effectively using academia as an aviation laboratory — and giving the engineers who may eventually design tomorrow's aircraft a chance to work on the problems before they become tomorrow's crises.

For aviation, that may be the most important part of the programme.