UT Austin is the lead institution for a AFOSR/NASA University Leadership Initiative program that focuses on developing a new measurement technology for hypersonic flight. This multi-university research and educational project is called FAST: Full-Airframe Sensing Technology for Hypersonic Aerodynamics Measurements. The FAST concept is that aerodynamic loads are “encoded” in the structural deformation of the vehicle, and so sufficiently accurate measurements of the deformation should enable the integrated and distributed aerodynamic pressure loads over the external surface of the vehicle.
You can find more information on FAST here.
Laboratory personnel: Brianna Blocher, Brandon Chavez, Ben Diaz Villa, Marc Eitner, Tarang Sane
Sponsor: AFOSR and NASA
In the FAST concept measurements of strain on the internal structure of a vehicle are used to solve an “inverse problem” to determine the aerodynamic loads that caused the deformation. To solve the inverse problem we will use scientific machine learning (SciML) combined with an accurate aerothermoelastic structural model of the vehicle. The SciML algorithm will be trained by imposing notional pressure distributions on the exterior of the simulated vehicle and computing its structural response. Thousands of simulated scenarios of applied forces and the structural response will be used for training. The aerothermoelastic structural response model will be validated using a combination of benchtop and wind tunnel experiments.
The FAST leadership team and the role of each member institution are as follows:
The University of Texas at Austin
Noel Clemens, PI
Experimental Validation: Prof. Jayant Sirohi and Prof. Noel Clemens
Scientific Machine Learning: Prof. Karen Willcox
Education and Workforce Development: Prof. Amanda Masino and Prof. Engin Topkara
University of Michigan
Aerothermoelastic structural simulation: Prof. Carlos Cesnik
University of Texas at San Antonio
Hypersonic aeroelastic model testing: Prof. Chris Combs
Sandia National Laboratories
High-fidelity CFD simulations and reduced-order modeling: Dr. Patrick Blonigan
Lockheed Martin Corporation
Hypersonic systems: Barry Bauer, Dr. John Rhoads, Michael Niestroy)