Introduction to the manual machine operation, CNC fabrication and usage of basic hand tools, band/hack saws, drill presses, grinders and sanders.
Elements of statics; dynamics of a particle and systems of particles.
Steady and unsteady heat conduction. Radiative heat transfer. Internal and external forced and free convective heat transfer. Change of phase. Heat exchangers.
Steady and unsteady heat conduction. Radiative heat transfer. Internal and external forced and free convective heat transfer. Change of phase. Heat exchangers.
Introduction to drafting, engineering graphics, computer graphics, solid modeling, and mechanical engineering design. Interactive computer graphics and numerical methods applied to the solution of mechanical engineering design problems.
Introduction to microstructures and properties of metals, polymers, ceramics and composites; typical manufacturing processes: material removal, shaping, joining, and property alteration; behavior of engineering materials in the manufacturing processes.
Research training course. Recommended in preparation for laboratory related research.
Enrollment limited to 12 students. Mechatronics is the application of electronics and microcomputers to control mechanical systems. Systems explored include on/off systems, solenoids, stepper motors, DC motors, thermal systems, magnetic levitation. Use of analog and digital electronics and various sensors for control. Programming microcomputers in Assembly and C. Lab required.
Connects basic MEMS transduction elements to applications by analyzing the analog signal chain, sensor packaging, and sensor integration into larger systems. Underlying concepts of analog instrumentation such as filtering and digitization covered. Hands-on projects involve off-the-shelf sensors and single-board computers to create self-contained sensor systems that demonstrate relevant issues.
Advanced classical thermodynamics. Availability, irreversibility, generalized behavior, equations of state for nonideal gases, mixtures and solutions, phase and chemical behavior, combustion. Thermodynamic properties of ideal gases. Applications to automotive and aircraft engines, refrigeration and air conditioning, and biological systems.
Principles of flight, incompressible flows, compressible regimes. Inviscid compressible aerodynamics in nozzles (wind tunnels, jet engines), around wings (aircraft, space shuttle) and around blunt bodies (rockets, reentry vehicles). Physics of normal shock waves, oblique shock waves, and explosion waves.
Historical co-evolution of building energy systems and fuels. Classifying existing buildings into typologies that are a prevalent combination of building size, age, fuels, equipment, distribution, and zoning controls. Fuels, electricity, furnaces, boilers, heat pumps. Overview of common heat
and hot water distribution systems. Case-study based approach to evaluate retrofit options for each typology. Considerations of location, stagingupgrades, envelope efficiency, retrofit cost structure, paybacks with a view towards decarbonization.
Introduction to kinematic analysis and design of machines and robots. Analytical and graphical synthesis of four-bar linkages. Planar displacements of rigid bodies. Spherical displacements of rigid bodies. Spatial displacements of rigid bodies. Rigid body velocities and wrenches. Concepts of kinematics of open-chain linkages.
Overview of robot applications and capabilities. Linear algebra, kinematics, statics, and dynamics of robot manipulators. Survey of sensor technology: force, proximity, vision, compliant manipulators. Motion planning and artificial intelligence; manipulator programming requirements and languages.
Additive manufacturing processes, CNC, Sheet cutting processes, Numerical control, Generative and algorithmic design. Social, economic, legal, and business implications. Course involves both theoretical exercises and a hands-on project.
Introduction to industrial automation technologies. Recognizing, modeling and integration of industrial automation problems. Hands-on experiments with robots, computer vision, data management and programming. Sensors engineering and measurement tools; process control; automation hardware and software architectures; programmable logic controllers.
Introduction to human spaceflight from a systems engineering perspective. Historical and current space programs and spacecraft. Motivation, cost, and rationale for human space exploration. Overview of space environment needed to sustain human life and health, including physiological and psychological concerns in space habitat. Astronaut selection and training processes, spacewalking, robotics, mission operations, and future program directions. Systems integration for successful operation of a spacecraft. Highlights from current events and space research, Space Shuttle, Hubble Space Telescope, and International Space Station (ISS). Includes team design project.
Prerequisite(s): Permission of the instructor. Topics and Instructors change from year to year. For advanced undergraduate students and graduate students in engineering, physical sciences, and other fields.
Prerequisite(s): Permission of the instructor. Topics and Instructors change from year to year. For advanced undergraduate students and graduate students in engineering, physical sciences, and other fields.
Interaction of light with nanoscale materials and structures for purpose of inducing movement and detecting small changes in strain, temperature, and chemistry within local environments. Methods for concentrating and manipulating light at length scales below the diffraction limit. Plasmonics and metamaterials, as well as excitons, phonos, and polaritons and their advantages for mechanical and chemical sensing, and controlling displacement at nanometer length scales. Applications to nanophotonic devices and recently published progress in nanomechanics and related fields.
Application of analytical techniques to the solution of multidimensional steady and transient problems in heat conduction and convection. Lumped, integral, and differential formulations. Topics include use of sources and sinks, laminar/turbulent forced convection, and natural convection in internal and external geometries.
Review of classical dynamics, including Lagrange’s equations. Analysis of dynamic response of high-speed machine elements and systems, including mass-spring systems, cam-follower systems, and gearing; shock isolation; introduction to gyrodynamics.
Analysis of stress and strain. Formulation of the problem of elastic equilibrium. Torsion and flexure of prismatic bars. Problems in stress concentration, rotating disks, shrink fits, and curved beams; pressure vessels, contact and impact of elastic bodies, thermal stresses, propagation of elastic waves.
Mechanics of nonlinear mechanical behavior of elastomeric and elastomeric-like solids. Overview of structure and behavior of elastomers. Kinematics of large deformation. Constitutive models for equilibrium stress-strain behavior, using invariant measures of deformation and statistical mechanics of molecular networks. Automated Constitutive Model Discovery via Neural Networks. Hysteretic aspects of structure and behavior due to time dependence and structural evolution with deformation. Review of experimental data and models to capture and predict observations. Time permitting: behavior of particle-filled, thermoplastic and biomacromolecular elastomers.
Advanced Linear Algebra, Complex Variable Theory, Integral Transforms, Measure Theory and Probability Theory, Advanced Information Theory, Differential and Difference Equations, Calculus of Variations, Nonlinear Optimization, State-Space Modeling, Advanced Signal Processing and Recognition: non-Stationary Signal Recognition, Spectral and Cepstral Analysis, Supervised and Unsupervised Clustering, Decision Theory, Math of modern NN architectures.
Robots using machine learning to achieve high performance in unscripted situations. Dimensionality reduction, classification, and regression problems in robotics. Deep Learning: Convolutional Neural Networks for robot vision, Recurrent Neural Networks, and sensorimotor robot control using neural networks. Model Predictive Control using learned dynamics models for legged robots and manipulators. Reinforcement Learning in robotics: model-based and model-free methods, deep reinforcement learning, sensorimotor control using reinforcement learning.