Abstract
This paper originates from the joint efforts of an aeroelastic study team in the Applied Vehicle Technology Panel from the NATO Science and Technology Organization, with the Task Group number AVT-191, titled “Application of Sensitivity Analysis and Uncertainty Quantification to Military Vehicle Design.” We present aeroelastic uncertainty quantification studies using the SemiSpan Supersonic Transport wind tunnel model at the NASA Langley Research Center. The aeroelastic study team decided treat both structural and aerodynamic input parameters as uncertain and represent them as samples drawn from statistical distributions, propagating them through aeroelastic analysis frameworks. Uncertainty quantification processes require many function evaluations to asses the impact of variations in numerous parameters on the vehicle characteristics, rapidly increasing the computational time requirement relative to that required to assess a system deterministically. The increased computational time is particularly prohibitive if high-fidelity analyses are employed. As a remedy, the Istanbul Technical University team employed an Euler solver in an aeroelastic analysis framework, and implemented reduced order modeling with Polynomial Chaos Expansion and Proper Orthogonal Decomposition to perform the uncertainty propagation. The NASA team chose to reduce the prohibitive computational time by employing linear solution processes. The NASA team also focused on determining input sample distributions.
Original language | English |
---|---|
Title of host publication | AIAA SciTech Forum - 55th AIAA Aerospace Sciences Meeting |
Publisher | American Institute of Aeronautics and Astronautics Inc. |
ISBN (Electronic) | 9781624104473 |
DOIs | |
Publication status | Published - 2017 |
Event | 55th AIAA Aerospace Sciences Meeting - Grapevine, United States Duration: 9 Jan 2017 → 13 Jan 2017 |
Publication series
Name | AIAA SciTech Forum - 55th AIAA Aerospace Sciences Meeting |
---|
Conference
Conference | 55th AIAA Aerospace Sciences Meeting |
---|---|
Country/Territory | United States |
City | Grapevine |
Period | 9/01/17 → 13/01/17 |
Bibliographical note
Publisher Copyright:© 2017 by Melike Nikbay, Jennifer Heeg.
Funding
The authors thank the S4T project and team for their work and willingness to share the modeling, data and prior simulation results. Their thorough work in the model tuning and the deterministic baseline analysis case greatly eased the preparatory tasks for the current work. The first author would like to thank the Istanbul Technical University Scientific Research Projects Center (BAP) for the research fund under the project titled “Computational Aeroelasticity Investigations for RTO-AVT-203 and
Funders | Funder number |
---|---|
Istanbul Technical University Scientific Research Projects Center | |
British Association for Psychopharmacology | RTO-AVT-203 |