1 - 10 of 29 results for: AA

This class introduces the basics of aeronautics and astronautics through applied physics, hands-on activities, and real world examples. The principles of fluid flow, flight, and propulsion for aircraft will be illustrated, including the creation of lift and drag, aerodynamic performance including takeoff, climb, range, and landing. The principles of orbits, maneuvers, space environment, and propulsion for spacecraft will be illustrated. Students will be exposed to the history and challenges of aeronautics and astronautics.

Computational methods are pervasive in analysis, design and optimization of aerospace systems. This course introduces the fundamental concepts underlying aerospace computational science. Starting from the concepts of meshes, elements and point clouds, interpolation, quadrature and time integration, the techniques of finite difference, finite volume and finite element discretization of general PDE problems, and analysis of the accuracy, consistency and stability of discretized problems including treatment of boundary conditions are developed. In depth applications to computations of ideal subsonic, transonic and supersonic flows, and viscous internal and external flow with a turbulence model are introduced. Through the use of commercial and research software (ANSYS Fluent, SU2 and AERO Suite) the student is exposed to the use of computational tools for solving practical aerospace engineering problems. The course culminates with the treatment of multidisciplinary aerospace problems involving coupling across more than one discipline, such as aero-thermal analysis (for hypersonic vehicle performance analysis or gas turbine blade cooling), fluid-structure interaction problems (such as flutter or flapping wing aeroelastic performance), and aeroacoustics (such as jet noise for next generation commercial supersonic transport or noise radiation from multi-rotor urban air mobility platform). Students are expected to pursue significant computational projects in two-person teams. nPrerequisites: CME102, CME104 (multivariable calculus, linear algebra, ODEs and some PDEs), ENGR 14, ME 30, ME70, and Recommended courses: AA102, AA103.

Preference to freshmen. Why people want to know where they are: answers include cross-Pacific trips of Polynesians, missile guidance, and distraught callers. How people determine where they are: navigation technology from dead-reckoning, sextants, and satellite navigation (GPS). Hands-on experience. How GPS works; when it does not work; possibilities for improving performance.

Space Capstone I. This course is focused on the design and implementation of uncrewed spacecraft with an emphasis on nano-satellites. Practical laboratory exercises will introduce students to the fundamentals of flight software, electronics, and mechanical design while building on a flight-proven spacecraft architecture. Students will work in teams to develop and present their design of a spacecraft subsystem. Required for Aero/Astro majors. For all other majors consent of instructor is required. Prerequisite: AA 131

Air Capstone II. Required for Aero/Astro majors. This capstone design class brings together the material from prior classes in a way that emphasizes the interactions between disciplines and demonstrates how some of the more theoretical topics are synthesized in practical design of an aircraft concept. The class will address a single problem developed by the faculty and staff. Students will spend two quarters designing a system that addresses the objectives and requirements posed at the beginning of the course sequence. They will work individually and in teams, focusing on some aspect of the problem but exposed to many different disciplines and challenges. The second quarter will focus on the demonstration of a physical system incorporating features of the design solution. This may be accomplished with a set of experiments or a flight demonstration involving data gathering and synthesis of work in a final report authored by the team.

This course is designed to prepare the student pilot to meet the Federal Aviation Administration (FAA) requirements (14 FAR 61.105) to take and pass (70% or greater score) the FAA Private Pilot Knowledge (written) exam. Topics include aerodynamics, airplane systems, performance and limitations, federal aviation regulations, navigation, aviation weather theory, flight planning, and risk management. Upon successful competition of this course, the instructor will endorse the appropriate section of your logbook to sit for the FAA Private Pilot Knowledge exam. Additionally, this course seeks to introduce the joys and opportunities that aviation can provide whether personal/pleasure flying, commercial flying or beyond.

This course teaches advanced principles for endowing mobile autonomous robots with capabilities to autonomously learn new skills and to physically interact with the environment and with humans. It also provides an overview of different robot system architectures. Concepts that will be covered in the course are: Reinforcement Learning and its relationship to optimal control, contact and dynamics models for prehensile and non-prehensile robot manipulation, imitation learning and human intent inference, as well as different system architectures and their verification. Students will earn the theoretical foundations for these concepts and implement them on mobile manipulation platforms. In homeworks, the Robot Operating System (ROS) will be used extensively for demonstrations and hands-on activities. Prerequisites: CS106A or equivalent, CME 100 or equivalent (for linear algebra), CME 106 or equivalent (for probability theory), and AA 171/274.

For undergraduates. Experimental or theoretical work under faculty direction, and emphasizing development of research and communication skills. Written report(s) and letter grade required; if this is not appropriate, enroll in 199. Consult faculty in area of interest for appropriate topics, involving one of the graduate research groups or other special projects. May be repeated for credit. Prerequisite: consent of instructor.