Reimagining Wing Foil Designs With a Desktop Modular Data Collection Wind Tunnel

Overview

The design of aircraft wings greatly impacts the efficiency of flight vehicles. With developments in CAD, 3D printing, and simulation, students are able to participate in wing design. However, effective wing design relies on validation through real-world, physical wind tunnel testing. Traditional large-scale wind tunnels are difficult for students to access, while small-scale wind tunnels are still expensive and often don’t include data collection. Therefore, this study aims to design a wind tunnel that can be used in school laboratories or at home to obtain authentic experimental data for wing testing and to validate its effectiveness through wing design. This research involved stages such as planning, data collection, design, construction, and programming of three prototype versions. Additionally, wing design helps the design of a more efficient wing design/feature using slits on the upper surface of a wing. Ultimately, a modular Data Collection Wind Tunnel was developed, capable of generating a wind speed of 3.7 m/s in the test area while collecting data on wind speed, wing lift, drag, and deformation. The whole size of the wind tunnel, including the fan, is 30 x 20 x 90cm, which can be easily placed on a table. Three wing models designed using Onshape were tested in the wind tunnel, generating valid data on lift, drag, and displacement. The wing with 3 symmetrical slits from the 60 to the 100 percent cord length was the most effective wing designed and tested, generating an average of 4.57 mN of drag, 373.63mN of Lift, and 3.53mm of shift. The results aligned closely with data from simulation software, validating the effectiveness of the wind tunnel. Although discrepancies between the wind tunnel data and simulation remain due to factors such as 3D printing accuracy and sensor precision, the wind tunnel can still serve as an effective tool for real-world validation of wing designs. Particularly in school laboratories or home settings, it provides an accessible data collection wind tunnel for general student use.

Competition history

• CSEF 2026 Applied Mechanics (Senior Division) · Entry S-02-16

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