Date of Award
Spring 2025
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Mechanical & Aerospace Engineering
Program/Concentration
Aerospace Engineering
Committee Director
Drew Landman
Committee Member
Colin Britcher
Committee Member
Gene Hou
Abstract
An automated propeller test capability for the ODU Low-Speed Wind Tunnel Facility is demonstrated; implementing automation improved both ease of testing and quality of results. An experiment was performed with and without automation to compare results. Prior to this effort, propeller RPM and airstream velocity were manually controlled, leading to time consuming experiments. The setpoint for RPM had to be adjusted at each run to compensate for changes in airstream velocity.
LabVIEW, a graphical programming software, was used to develop the controllers and automation algorithm. A Proportional Integral Derivative (PID) control approach was developed to simultaneously control airstream velocity and propeller RPM. An automation algorithm was also developed to perform a series of runs, leveraging the PID controllers to minimize the need for user input. The algorithm supported general serial testing, and Design of Experiment (DOE) -based design approaches.
The comparison between manual and automated experiments followed the same restricted randomization experimental design developed in statistical design software; both experiments used identical set points and identical tools were used to simplify the regression model.
The automated experiment provided more precise results, resulting in a higher order model than the manual experiment. The measured advance ratios for the automated experiment deviated less from the nominal values than the manual experiment. Furthermore, the majority of verification runs on the automated experiment fell within the prediction interval whereas most responses on the manual experiment did not.
Rights
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DOI
10.25777/4n02-nw36
ISBN
9798280748026
Recommended Citation
Lara, David R..
"Wind Tunnel Automation For Propeller Testing"
(2025). Master of Science (MS), Thesis, Mechanical & Aerospace Engineering, Old Dominion University, DOI: 10.25777/4n02-nw36
https://digitalcommons.odu.edu/mae_etds/775
ORCID
0009-0005-5873-8715