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.

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. Enrollment priority will be given to Aero/Astro seniors. Prerequisite: AA 131

Air Capstone I. Required for Aero/Astro majors. This capstone design class allows students to apply knowledge from prior classes in a way that emphasizes the interactions between disciplines and demonstrates how theoretical topics are synthesized in the practical design of an aircraft concept. Prerequisites are MATH 19, 20, 21, CME 100, CME 102 or MATH 51, 53. CME 104 or Math 52 recommended. Elementary physics, and AA100 or equivalent classes. Additional required AA courses dealing with aero, structures, and controls.

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.

For undergraduate students. Educational opportunities in high technology research and development labs in industry. Students engage in internship work and integrate that work into their academic program. Following internship work, students complete a research report outlining work activity, problems investigated, key results, and follow-up projects they expect to perform. Meets the requirements for curricular practical training for students on F-1 visas. Student is responsible for arranging own internship/employment and faculty sponsorship. Register under faculty sponsor's section number. All paperwork must be completed by student and faculty sponsor, as the Student Services Office does not sponsor CPT. Students are allowed only two quarters of CPT per degree program. Course may be repeated twice.

Directed reading, lab, or theoretical work for undergraduate students. 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.

Topics: development of the three-dimensional, unsteady, field equations for describing the motion of a viscous, compressible fluid (Euler and Navier-Stokes equations); entropy condition; jump equations for normal shock; linear acoustic wave; Riemann problem; unsteady one-dimensional flow; eigenvalues and characteristics; shock tube; area-averaged equations for one-dimensional steady flow; channel flow with heat addition and friction; flow in nozzles and inlets; steady supersonic flow in two-dimensions; oblique shock waves; Prandtl-Meyer expansion; small disturbance theory; potential flow; lift and drag of thin airfoils. Prerequisites: undergraduate background in fluid mechanics and thermodynamics.

Analysis and design techniques for multivariable feedback systems. State-space concepts, observability, controllability, eigenvalues, eigenvectors, stability, and canonical representations. Approaches for robust feedback control design, chiefly H2, H-infinity, and mu-synthesis. System identification and adaptive control design. Use of computer-aided design with MATLAB. Prerequisite: ENGR 105, ENGR 205. Recommended: Linear algebra (EE 263 or equivalent).

Survey of recent research advances in intelligent decision making for dynamic environments from a computational perspective. Efficient algorithms for single and multiagent planning in situations where a model of the environment may or may not be known. Partially observable Markov decision processes, approximate dynamic programming, and reinforcement learning. New approaches for overcoming challenges in generalization from experience, exploration of the environment, and model representation so that these methods can scale to real problems in a variety of domains including aerospace, air traffic control, and robotics. Students are expected to produce an original research paper on a relevant topic. Prerequisites: AA 228/CS 238 or CS 221.

Continuation of AA 236A. This course focuses on the design and implementation of spacecraft deployable structure systems. Students will work in teams to propose a solution for a large deployable structure for small satellites. Students will demonstrate that their design meets functional, mechanical, and environmental requirements using analysis, prototyping, and testing. Prerequisite: AA 236A or consent of instructor.

Analyses of solid and thin walled section beams, trusses, frames, rings, monocoque and semimonocoque structures. Determination of stresses, strains, and deformations, and failure in structures; structural stability and buckling; material behavior: plasticity and fracture. Emphasis on energy methods and introduction of finite element methods. Prerequisite: ENGR 14 or equivalent.

First part of a two-quarter course dealing with multidisciplinary aspects of new aircraft systems development, emphasizing commercial aircraft. AA241A focuses on the vehicle design requirements, fuselage layout, low and high-speed aerodynamics, wing design, and aircraft stability/control, while AA241B deals with propulsion, structures, loads, mission performance, and economics. Students choose a set of economic goals and environmental constraints, developing their own designs individually. To obtain the maximum benefit from this course sequence, students are encouraged to enroll in both courses in consecutive quarters. Prerequisites : undergraduate and/or graduate courses in aerodynamics, aircraft design, or equivalent.

Physics and engineering of plasmas, including space and laboratory plasmas. Debye length and distribution functions. Single-particle motion and drifts. Plasmas as fluids and fluid drifts. Waves in plasmas, including electrostatic and electromagnetic. Diffusion and resistivity. Magnetohydrodynamics.

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.

Navigation is a key element in many autonomous systems, from self-driving cars to aerial taxis and space robots. In this course you will learn about sensors and algorithms that enable autonomous localization and navigation. Topics include GPS system design and absolute positioning; fault robustness and navigation integrity; odometry and simultaneous localization and mapping (SLAM) using filtering and graph optimization; vision and LiDAR-based navigation; and deep learning for perception and scene representation. Prerequisites: AA 222, EE 278 and EE 263. Recommended: AA 272, EE 261, AA 273, AA228.

Orbits of near-earth satellites and interplanetary probes; relative motion in orbit; transfer and rendezvous; orbit determination; influence of earth's oblateness; sun and moon effects on earth satellites; decay of satellite orbits; invited lectures from industry. Prerequisite: ENGR 15 and familiarity with MatLab.

Seminar talks by researchers and industry professionals on topics related to modern robotics and autonomous systems. Broadly, talks will cover robotic design, perception and navigation, planning and control, and learning for complex robotic systems. May be repeated for credit.

(Undergraduates register for 190 or 199.) Experimental, theoretical, or computational investigation. Students may work in any field of special interest. This course is designed to develop students' understanding of what a research problem is and the skills needed to successfully approach and conduct research. Register in Axess for section belonging to your research supervisor once the faculty member agrees to supervise your independent study. May be repeated for credit.

Educational opportunities in high-technology research and development labs in aerospace and related industries. Internship integrated into a student's academic program. Research report outlining work activity, problems investigated, key results, and any follow-on projects. Meets the requirements for Curricular Practical Training for students on F-1 visas. Student is responsible for arranging own employment and should see department student services manager before enrolling. May be repeated for credit.

Guest speakers present research related to plasma science and engineering, ranging from fundamental plasma physics to industrial applications of plasma.

Thesis for degree of Engineer. Students register for section belonging to their thesis adviser.

Prerequisite: completion of Ph.D qualifying exams. Students register for section belonging to their thesis adviser. (Staff)

Engineer's thesis or non-doctoral work for a TGR student.

Doctoral dissertation for a TGR student in PhD program.