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Computational validation and system identification modeling for stability and control predictions

Published online by Cambridge University Press:  15 December 2022

M. Ghoreyshi Open the ORCID record for M. Ghoreyshi [Opens in a new window] ,
A. Jirasek  and
J. Seidel Open the ORCID record for J. Seidel [Opens in a new window]
M. Ghoreyshi*
Affiliation:
High Performance Computing Research Center, U.S. Air Force Academy Department of Aeronautics USAF Academy Colorado 80840, USA
A. Jirasek
Affiliation:
High Performance Computing Research Center, U.S. Air Force Academy Department of Aeronautics USAF Academy Colorado 80840, USA
J. Seidel
Affiliation:
High Performance Computing Research Center, U.S. Air Force Academy Department of Aeronautics USAF Academy Colorado 80840, USA
*
*Correspondence author. Email: Mehdi.Ghoreyshi@usafa.edu
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Abstract

This article presents the results of the first AIAA Stability and Control Prediction Workshop obtained at the U.S. Air Force Academy using the kCFD flow solver of the ${\rm{HPCMP}}\;{\rm{CREAT}}{{\rm{E}}^{{\rm{TM}}}}$-AV Kestrel simulation tools. The test case considered is a large-scale Common Research Model (CRM) tested at the ONERA S1MA wind tunnel at different transonic speeds and fixed lift coefficient values at zero and non-zero side-slip angles. The computational results include a grid sensitivity analysis and validation with available experimental data. In addition, the Mach number and sting effects on the predicted stability and control values of the test case are investigated. Finally, a system identification method using a regression model is developed and used for prediction of stability and control data. The regression coefficients are estimated from an input signal with varying-frequency changes in the angle-of-attack, pitch rate, and side-slip angle. Once the model was created, it was used to predict the static and dynamic aerodynamic data of the test cases. The results show that the model predictions match very well with calculated CFD data at discrete flow conditions.

Keywords

Stability and controlSystem identificationCFD

Information

Type
Research Article
Information
The Aeronautical Journal , Volume 127 , Issue 1311 , May 2023 , pp. 831 - 851
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Creative Commons
This is a work of the US Government and is not subject to copyright protection within the United States. Published by Cambridge University Press on behalf of Royal Aeronautical Society
Copyright
© United States Government, 2022

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Distribution A. Approved for Public Release. Distribution unlimited.

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