Aerodynamics is an important aspect of UAS design because it is directly related to fuel efficiency and safety. Traditional aerodynamic design heavily relies on human intuition and experience. This human-supervised process is slow and conflicts with the ever-increasing expectation for timely high-performance UAS designs. Given the above background, this LAUNCH project’s objective is to use the state-of-the-art aerodynamic optimization technique to improve the aerodynamic performance of a UAS wing automatically. The automated optimization is achieved by first simulating three-dimensional flow fields and aerodynamic objectives (e.g., drag, lift, and moment) using computational fluid dynamics (CFD). Then, an adjoint solver is used to compute the gradients of objectives. The objective values and gradients will be given to an optimizer to determine a new, improved wing shape automatically. The above process will be repeated until satisfactory performance improvement is obtained. Because of its potential in reducing the design period, aerodynamic design optimization has increased interest in academia and industry.
The LAUNCH students will work with the project mentor to run the aerodynamic optimization, post-processing the optimization results, and summarize the research. After the project, the students will be able to learn how to:
- Generate a CFD mesh for the UAS wing;
- Run CFD simulations to predict aerodynamic performance;
- Run gradient-based aerodynamic optimization to improve the design performance automatically.
- Extract flow information (e.g., velocity and pressure) from the simulation results;
- Interpret the underlying physics that drives the design improvement;
- Write a scientific report to summarize the research results.
Project Mentor: Dr. Ping He