While low disturbance (“quiet”) hypersonic wind tunnels are believed to provide more reliable extrapolation of boundary layer transition behavior from ground to flight, the presently available quiet facilities are limited to Mach 6, moderate Reynolds numbers, low freestream enthalpy, and subscale models. As a result, only conventional (“noisy”) wind tunnels can reproduce both Reynolds numbers and enthalpies of hypersonic flight configurations, and must therefore be used for flight vehicle test and evaluation involving high Mach number, high enthalpy, and larger models. This article outlines the recent progress and achievements in the characterization of tunnel noise that have resulted from the coordinated effort within the AVT-240 specialists group on hypersonic boundary layer transition prediction. New Direct Numerical Simulation (DNS) datasets elucidate the physics of noise generation inside the turbulent nozzle wall boundary layer, characterize the spatiotemporal structure of the freestream noise, and account for the propagation and transfer of the freestream disturbances to a pitot-mounted sensor. The new experimental measurements cover a range of conventional wind tunnels with different sizes and Mach numbers from 6 to 14 and extend the database of freestream fluctuations within the spectral range of boundary layer instability waves over commonly tested models. Prospects for applying the computational and measurement datasets for developing mechanism-based transition prediction models are discussed.
|Original language||English (US)|
|Title of host publication||AIAA Aerospace Sciences Meeting|
|Publisher||American Institute of Aeronautics and Astronautics Inc, AIAA|
|State||Published - 2018|
|Event||AIAA Aerospace Sciences Meeting, 2018 - Kissimmee, United States|
Duration: Jan 8 2018 → Jan 12 2018
|Name||AIAA Aerospace Sciences Meeting, 2018|
|Other||AIAA Aerospace Sciences Meeting, 2018|
|Period||1/8/18 → 1/12/18|
Bibliographical noteFunding Information:
This work was sponsored by the Air Force Office of Scientific Research (under grants FA9550-14-1-0170, FA9550-17-1-0250, and FA9550-12-1-0167). Computational resources were provided by the DoD High Performance Computing Modernization Program, the NASA Advanced Supercomputing Division, and the NSF PRAC program (NSF ACI-1640865). Eric Marineau would like to acknowledge the Test Resource Management Center T&E / S&T HSST program for their funding as part of the Center of Testing Excellence. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the funding agencies or the U.S. Government. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.