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This course is concerned with the design analysis of gas-turbine engines. After reviewing essential concepts of thermo- and aerodynamics, we consider a turbofan gas-turbine engine that is representative of a business aircraft. We will first conduct a performance analysis to match the engine design with aircraft performance requirements. This is followed by examining individual engine components, including compressor, combustor, turbines, and nozzles, thereby increase the level of physical description. Aspects of modern engine concepts, environmental impacts, and advanced engine-analysis methods will be discussed. Students will have the opportunity to develop a simulation code to perform a basic design analysis of a turbofan engine.

Linear-elastic and elastic-plastic fracture mechanics from a materials science perspective, emphasizing microstructure and the micromechanisms of fracture. Plane strain fracture toughness and resistance curve behavior. Mechanisms of failure associated with cohesion and adhesion in bulk materials, composites, and thin film structures. Fracture mechanics approaches to toughening and subcritical crack-growth processes, with examples and applications involving cyclic fatigue and environmentally assisted subcritical crack growth. Prerequisite: 151/251, 198/208, or equivalent. SCPD offering.

Students design and fabricate a highly refined chair. The process is informed and supported by historical reference, anthropometrics, form studies, user testing, material investigations, and workshops in wood steam-bending, plywood forming, metal tube bending, TIG & MIG welding, upholstery & sewing. Prerequisite: ME103/203 or consent of instructor. May be repeated for credit. By application only, see notes below.

The time of robotics/AI is upon us. Within the next 10 to 20 years, many jobs will be replaced by robots/AI (artificial intelligence). This seminar features guest lecturers from industry and academia discussing the current state of the field of robotics/AI, preparing students for the rise of robotics/AI, and redesigning and reinventing education to adapt to the new era.

We investigate Learning and Making environments that enable participants to learn technical concepts through designing and prototyping at low cost. The course consists of lectures, invited guest talks and a final project. Students interact with guest speakers who have developed novel learning environments and deployed them in mainstream education settings as well as in extreme conditions such as remote rural locations. Students work in teams to complete a course project using design methodology to develop a learning environment solution.

Basic principles for endowing mobile autonomous robots with perception, planning, and decision-making capabilities. Algorithmic approaches for robot perception, localization, and simultaneous localization and mapping; control of non-linear systems, learning-based control, and robot motion planning; introduction to methodologies for reasoning under uncertainty, e.g., (partially observable) Markov decision processes. Extensive use of the Robot Operating System (ROS) for demonstrations and hands-on activities. Prerequisites: CS 106A or equivalent, CME 100 or equivalent (for linear algebra), and CME 106 or equivalent (for probability theory).

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.

This course empowers you with the design process and confidence needed to tackle mechanical design challenges similar to those seen in industry. We will cover valuable design, manufacturing, assembly, and machine design content which you will apply to the weekly projects. These projects are simplified yet representative versions of typical mechanical design challenges seen in industry. You will submit authentic deliverables, such as cad models and technical drawings, and present those deliverables live in a 'design review' format. With frequent feedback, reflection, revision, and repetition, you will refine these professional skills. By successfully completing this course you will bridge the gap between the lessons learned in school and the professional capabilities expected to be an effective engineer in industry.

Experimental techniques to study human and animal movement including motion capture systems, EMG, force plates, medical imaging, and animation. The mechanical properties of muscle and tendon, and quantitative analysis of musculoskeletal geometry. Projects and demonstrations emphasize applications of mechanics in sports, orthopedics, and rehabilitation.