Aerospace engineers apply scientific principles and engineering concepts and practices to design, build, test, analyze, operate and maintain man-made things that fly, including airplanes with fixed wings, helicopters, missiles, launch vehicles, and manned and unmanned spacecraft. They may work as members of research teams, manage technical and research staffs, become test pilots, astronauts, CEOs of airlines or own their own companies, continue on to professional schools and become medical doctors, lawyers, or professors.
Auburn University's Department of Aerospace Engineering provides a balanced undergraduate education in aeronautics and astronautics leading to a Bachelor of Aerospace Engineering degree. Students study math and science as well as aerospace fundamentals such as aerodynamics, the dynamics of flight, propulsion and structures, and design.
Graduate programs lead to the Master of Science, Master of Aerospace Engineering, and Doctor of Philosophy degrees. Students may specialize in aerodynamics, orbital mechanics, spacecraft dynamics and control, atmospheric flight dynamics and control, propulsion, structures, or structural dynamics. Aerospace engineering faculty members are engaged in a wide variety of research and outreach activities. The department is home to the Adaptive Aerostructures Laboratory, Aerodynamics Laboratory, Missile and Aircraft Hardware-in-the-Loop Simulation Lab, Composite Materials Laboratory, Flight Dynamics and Control Laboratory, Laser Diagnostics Laboratory, Flow Visualization Laboratory, and Structures and Structural Dynamics Laboratory.
Research areas include the design of submersible aircraft, applications of computational fluid dynamics to model helicopter rotor/fuselage aerodynamics, nonintrusive flow diagnostics using high-speed switching lasers, flight dynamics and simulation of fixed- and rotary-wing manned and unmanned aircraft, and launch vehicle dynamics and control. A currently very popular area is the design of missiles and launch vehicles using modeling and simulation coupled with genetic algorithms to search for optimal design parameters.
