This video showcases our activities in action, including the foam airplane flying, the drone identifying colors, our rocket in launch (second time), and the string test!

Rockets

Problem: Our team was challenged to design, build, test, and analyze several aerospace engineering projects involving rockets, drones, airplanes, and air quality monitoring. We designed and launched a single-stage rocket, compared its flight performance to a RockSim simulation, programmed a drone in Python to detect colored landing pads, modified a foam airplane with a propeller to maximize altitude and distance, and collected air quality data using environmental sensors. Throughout the project, we applied the engineering design process by identifying problems, testing solutions, and improving our designs based on data.

Prototypes/Ideas: Before building our final rocket, we completed several prototype activities to better understand flight and aerodynamics. We designed and tested paper airplanes with different wing shapes to observe how lift, drag, thrust, and stability affected flight. We also built compressed-air paper rockets and experimented with different fin sizes, nose cone shapes, and body lengths to see how each design changed the rocket's performance. Before constructing our single-stage rocket, we modeled and simulated it in RockSim while calculating the center of mass (CM) and center of pressure (CP) to predict whether the rocket would fly stably. These activities gave us a better understanding of how weight distribution and aerodynamics affect flight before building our final design.

Design/Test:  After constructing our single-stage rocket, we completed the string test to evaluate its stability. The purpose of the string test was to determine whether the center of pressure and center of mass were properly aligned for stable flight. The first time we did the string test, our center of mass and center of pressure were too far away from each other. When we launched the rocket, it shot up but then curved instead of going straight up, showing that it was unstable. Because of this, we rebuilt our rocket and repeated the string test multiple times while making adjustments. We modified the design until the center of mass and center of pressure were much closer together, which improved the rocket’s stability. For the drone project, we programmed the drone in Python to detect different colored landing pads. At first, we had an issue with the color detection because the drone was identifying red as every color. To fix this, we moved the drone around to collect better color samples and adjusted the code. We continued testing and making changes until the drone was able to correctly detect each color consistently. For the air quality project, we used sensors to collect environmental data around campus. We took about an hour-long walk around campus while gathering data using the sensors. After collecting the data, we imported it into MATLAB and modeled it to analyze patterns in air quality.

Evaluate/Improve: After each round of testing, we evaluated our results and made improvements based on the data we collected. Repeating the string test after every rocket modification helped us verify that changes to the center of mass and center of pressure improved stability. Rebuilding the rocket and adjusting its design resulted in a much more stable flight compared to our first launch. For the drone, repeated testing and collecting better color samples solved the color detection issue and improved the program’s accuracy. For the air quality project, modeling the data in MATLAB helped us better understand trends in the environment. This project reinforced the importance of careful planning, repeated testing, troubleshooting, and continuous improvement throughout the engineering design process.

MATLabs graphs for air quality ⬆️