Introduction to the manual machine operation, CNC fabrication and usage of basic hand tools, band/hack saws, drill presses, grinders and sanders.
Experiments in engineering and physical phenomena: aerofoil lift and drag in wind tunnels, laser Doppler anemometry in immersed fluidic channels, supersonic flow and shock waves, Rankine thermodynamical cycle for power generation, and structural truss mechanics and analysis.
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.
Building on the preliminary design concept, the detailed elements of the design process are completed: systems synthesis, design analysis optimization, incorporation of multiple constraints, compliance with appropriate engineering codes and standards, and Computer Aided Design (CAD) component part drawings. Execution of a project involving the design, fabrication, and performance testing of an actual engineering device or system.
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.
Independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, but no more than 3 points may be counted toward degree requirements. Projects requiring machine-shop use must be approved by the laboratory supervisor. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
Independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, but no more than 3 points may be counted toward degree requirements. Projects requiring machine-shop use must be approved by the laboratory supervisor. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
Independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, but no more than 3 points may be counted toward degree requirements. Projects requiring machine-shop use must be approved by the laboratory supervisor. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
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.
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. 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.
The course studies control strategies and their implementation in the discrete domain. Introduction with examples; review of continuous control and Laplace Transforms; review of continuous state-space representation and Solutions; review of difference equations, discretization in time and frequency, the WKS (aka Shannon) sampling theorem, windowing, filters, Transforms: Fourier series, Fourier transform, z-transform and their inverses; Ideal sampler, Sample-and-hold devices, zero, one, polygonal, and slewer hold; Transfer functions, block diagrams, and signal flow graphs for discrete systems; Discrete State-Space transformation, controllabililty, observability, and stability in the state-space domain. Discrete time and z domain analysis, steady state analysis, discrete-time root-locus, and pole-zero placement; Discrete Nyquist stability criterion, Bode plot, Gain and Phase Margin analysis, Nichols chart, bandwidth and sensitivity analysis; Design criteria, self-tuning regulator, Kalman filter, and simulation, followed by advanced stability analysis such as Lyapunov stability; Overview of the discrete Euler-Lagrange equations, discrete maximum and minimum principle, optimal linear discrete regulator design, optimality and dynamic programming.
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.
Fundamentals of sustainable design and manufacturing, metrics of sustainability, analytical tools, principles of life cycle assessment, manufacturing tools, processes and systems energy assessment and minimization in manufacturing, sustainable manufacturing automation, sustainable manufacturing systems, remanufacturing, recycling and reuse.
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 a design project to assist International Space Station astronauts.
Master's level independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, subject to Master's Program guidelines. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
Master's level independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, subject to Master's Program guidelines. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
Master's level independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, subject to Master's Program guidelines. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
Master's level independent project involving theoretical, computational, experimental, or engineering design work. May be repeated, subject to Master's Program guidelines. Students must submit both a project outline prior to registration and a final project write-up at the end of the semester.
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.
Development of governing equations for mixtures with solid matrix, interstitial fluid, and ion constituents. Formulation of constitutive models for biological tissues. Linear and nonlinear models of fibrillar and viscoelastic porous matrices. Solutions to special problems, such as confined and unconfined compression, permeation, indentation and contact, and swelling experiments.
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.
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.
Theoretical or experimental study or research in graduate areas in mechanical engineering and engineering science.