Engineering Students in NASA-UT Hypersonics Project Aim to Transform Sensing for High-Speed Vehicles

Internal sensors will give new insight into how hypersonic vehicles’ shapes distort under high forces.

(Image courtesy of The University of Texas at Austin Cockrell School of Engineering.)

(Image courtesy of The University of Texas at Austin Cockrell School of Engineering.)

NASA’s University Leadership Initiative has funded a new project to redefine sensing for hypersonic vehicles. Hypersonic vehicles are vehicles that can reach at least Mach 5, which is five times the speed of sound. The goal is to design sensors that can treat the vehicles themselves as a sensor.

This is a three-year project that will include four universities. The University of Texas will lead the project. Its San Antonio location has a Mach 7 wind tunnel, which will be instrumental in testing the technology at high speeds.

Creating sensors for hypersonic vehicles has been challenging. Traveling at such high speeds creates a lot of friction, which heats the vehicle and can burn up sensors placed on the outside of the vehicle. In this project, the team plans on creating internal sensors that can monitor the physical shape of the vehicle to gain real-time insights into the forces acting on the vehicle.

“We are taking conventional sensors and distributing them across the vehicle, allowing them to make measurements they weren’t meant to make,” explained Noel Clemens, the leader of the project and professor of Aerospace Engineering and Engineering Mechanics, in a statement. “By getting information from all the sensors simultaneously, we will be able to analyze the shape of the vehicle and infer the distribution of forces acting on the vehicle.”

Understanding how forces change the shape of hypersonic vehicles will improve our ability to control such vehicles. The extreme force of traveling at high speeds has altered the shapes of vehicles in ways that have caused their trajectories to change while traveling. A real-time account of such deformations could assist in correcting flight paths.

“Usually, it’s not possible to measure information like surface forces and torques while a vehicle is in flight,” said Jayant Sirohi, associate professor of Aerospace Engineering and Engineering Mechanics. “This information can be used to validate computer models and to help control the vehicle when it encounters uncertain conditions.”

The University of Michigan, one of the universities contributing to the project, will develop computational models to gain insight into how the deformations are caused in relation to force. However, this project is not just limited to universities with established engineering departments.

The University of Texas team will be collaborating with Huston-Tillotson University, which is located in Austin. Huston-Tillotson University has 1,100 undergraduate students and is working to create its own engineering program. Currently, it offers a pre-engineering program in partnership with Prairie View A&M.

For each of the three years of the project, three to five students from Huston-Tillotson University will be selected to work on the project. This partnership is designed not only to give valuable experience to the students but also to improve the project by increasing the diversity of the team.

Huston-Tillotson University is a historically Black university. As of 1952, the university has not had a restriction based on race, but it still plays an important role in introducing traditionally underrepresented people to engineering. The university has a significantly large percentage of Black and Hispanic students.

“Assumptions about why work is being done and how data is collected and applied will always be biased by experience,” said Amanda Masino, director of Huston-Tillotson’s STEM Research Scholars program. “Having a diverse team with different perspectives ensures that bias in collecting and deploying data is minimized.”

The team is currently focusing on designing and building computational models. They will have to create experimental models of hypersonic vehicles and develop machine learning programs that can discover the relationships between pressure and the deformation of the vehicles. Testing an actual vehicle is a couple of years away at this point. In the meantime, the students have a lot to discover.