In our project we analyzed the flutter of airfoils, more specifically, seeing how airspeed, different masses, and different mass moments of inertia affect flutter. To do this analysis, we collected experimental data from a wind tunnel and compared it to a mathematical model using a system of 2nd order ODEs.
The purpose of this project is to better understand the dynamics of airfoil flutter and share this information with people interested in aerodynamic oscillatory behavior.
We conducted our physical experiments using an Olin's H6910-12 wind tunnel, overseen by Olin professor Chris Lee, and a flutter analysis test rig created by Olin professors and students.
For our mathematical approach, we used a system of 2nd order ODEs, which are explained in more detail in the "motion model". For ease of speedy analysis, we created a python program to automate solving the characteristic equations for critical airspeed and flutter frequency.
We measured the oscillations of the airfoil plunge using an accelerometer which was attached to the rig to read the sensor information. We chose the Arduino Nano 33 BLE, which has a built-in IMU.
We collected data by connecting directly to the Arduino over USB and commanding it to read and transmit acceleration data over the serial port. In a separate python script, we read the serial output and saved the data to a file to be read back later.
Reference [3]
Analyze flutter data at different moments of inertia, masses, and wind speed
Find the frequency of airfoil oscillation data
Explain what type of system we are analyzing (underdamped, overdamped, no damping)
Gain wind tunnel experience
Understand the effect of wind speed on flutter
Find a way to determine critical flutter speed