Mechanical Engineering

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  • ENG ME 690: Advanced Product Design
    An eight credit, two term course. Advanced Product Design is focused on the tools and skills driving smart engineering decisions which anticipate user, societal and technological trends. A "proactive" mechanical engineer creates products and systems that are appropriate, effective, fail-resistant, and economically successful. Students are expected to perform original research on design and engineering trends, apply advanced engineering methods to case studies, defend their conclusions, and ultimately create a manufacturable design prototype.
  • ENG ME 691: Advanced Product Design and Engineering
    Fall Semester; part of a two-term sequence with ENG ME 692 Advanced Product Design and Engineering is focused on the tools and skills enabling smart, practical product engineering choices. A "proactive" mechanical engineer creates products and systems that are functional, manufacturable and economically successful, even as user expectations and technologies evolve. Students are expected to perform original research on design and engineering trends, apply advanced engineering methods to specific examples, justify their their conclusions in design reviews, and ultimately create a manufacturable design prototype. Grading based on a mix of team and individual assignments.
  • ENG ME 692: Advanced Product Design and Engineering
    Spring Semester; part of a two-term sequence with ENG ME 691. Advanced Product Design and Engineering is focused on the tools and skills enabling smart, practical product engineering choices. A "proactive" mechanical engineer creates products and systems that are functional, manufacturable, and economically successful, even as user expectations and technologies evolve. Students are expected to perform original research on design and engineering trends, apply advanced engineering methods to specific examples, justify their conclusions in design reviews, and ultimately create a manufacturable design prototype. Grading based on a mix of team and individual assignments.
  • ENG ME 700: Advanced Topics in Mechanical Engineering
    Specific prerequisites vary according to research topic.
  • ENG ME 701: Optimal and Robust Control
    This course is aimed at an introduction (with rigorous treatment) to the fundamentals of optimal and robust control. It will be divided roughly into two parts. The first will cover aspects of robust control including model reduction, H_2 and H_ infinity control, and feedback control of uncertain systems. The second will delve into optimal control including topics such as the linear quadratic regulator, the calculus of variations, the maximum principle, and the Hamilton-Jacobi-Bellman equation. Same as ENG EC 701 and ENG SE 701. Students may not receive credits for both.
  • ENG ME 702: Computational Fluid Dynamics
    Numerical techniques for solving the Navier-Stokes and related equations. Topics are selected from the following list, although the emphasis may shift from year to year: boundary integral methods for potential and Stokes flows; free surface flow computations; panel methods; finite difference, finite element and finite volume methods; spectral and pseudo-spectral methods; vortex methods; lattice-gas and lattice-Boltzmann techniques; numerical grid generation.
  • ENG ME 710: Dynamic Programming and Stochastic Control
    Introduction to sequential decision making via dynamic programming. The principle of optimality as a unified approach to optimal control of dynamic systems and Markovian decision problems. Applications from control theory and operations research include linear-quadratic problems, the discrete Kalman Filter, inventory control, network, investment, and resource allocation models. Adaptive control and numerical solutions through successive approximation and policy iteration, suboptimal control, and neural network applications involving functional approximations and learning. Same as ENG EC 710 and ENG SE 710. Students may not receive credits for both.
  • ENG ME 712: Applied Mathematics in Mechanics
    The goal of this course is to give students an introduction to mathematical tools for solving difficult mathematics problems that arise in engineering science and mechanics. Students will learn the process of applied mathematics, which will enable them to take a hard problem, and gain insight into its important characteristics. Analytical theory, approximate techniques, and numerical methods will be used in a complementary manner to solve challenging engineering problems. Students will learn dimensional analysis and scaling, perturbation methods applied to polynomial and differential equations, variational calculus, integral equations, and concepts of stability and bifurcation. Students will apply these methods to mathematical problems in solid mechanics, thermodynamics, and dynamical systems.
  • ENG ME 714: Advanced Stochastic Modeling and Simulation
    Introduction to Markov chains, point processes, diffusion processes as models of stochastic systems of practical interest. The course focuses on numerical and simulation methods for performance evaluation, optimization, and control of such systems. Same as ENG SE 714. Students may not receive credits for both.
  • ENG ME 720: Acoustics II
    Wave equation in cylindrical and spherical co-ordinate systems. Propagation in waveguides. Diffraction: the Rayleigh integral and the Helmholtz-Kirchhoff integral. Green's function and angular spectrum methods. Diffraction of sound beams: Guassian beams, unfocused and focused sources, and arrays. Diffraction by apertures, discs and wedges. Scattering of sound; Rayleigh scattering, scattering cross-section, elastic scatters. Propagation in inhomogeneous media: rays, the eikonal equation, the Blokhintzev invariant and the acoustic field near caustics. Absorption and dispersion of acoustic waves. Transmission and reflection at a fluid-solid interface.
  • ENG ME 721: Acoustic Bubble Dynamics
    Bubbles and acoustic cavitation play an important role in many aspects of application of sonic and ultrasonic energy in fluids and biological tissue. This course will introduce the study of bubble phenomena in sound fields. The fundamental physical acoustics of bubbles (and the fundamental physics which can be illustrated by the study of bubble dynamics) will be stressed. The family of Rayleigh-Plesset equations for time-dependent bubble behavior will be derived from the Navier-Stokes equations. Analytical approximations to the Rayleigh-Plesset equations in limiting cases will be derived and studied. Approximations to the thermodynamic behavior of oscillating bubbles will be considered in detail. Thermal, acoustic and viscous contributions to dissipation will be treated. Numerical solutions will also be studied, specifically in the context of highly nonlinear behavior during acoustically-forced oscillations. Specific experiments, and experimental techniques for measuring bubble dynamics will be studied in detail. Topics covered will contrast agent microbubbles, acoustics of bubbly liquids, bubble-mediated bioeffects, shape instabilities, acoustic levitation, sonoluminescence, heat and mass transfer during bubble oscillations, sonochemistry and cavitation detection and monitoring.
  • ENG ME 724: Advanced Optimization Theory and Methods
    Complements ENGEC524 by introducing advanced optimization techniques. Emphasis on nonlinear optimization and recent developments in the field. Topics include: unconstrained optimization methods such as gradient and incremental gradient, conjugate direction, Newton and quasi-Newton methods; constrained optimization methods such as projection, feasible directions, barrier and interior point methods; duality; and stochastic approximation algorithms. Introduction to modern convex optimization including semi-definite programming, conic programming, and robust optimization. Applications drawn from control, production and capacity planning, resource allocation, communication and sensor networks, and bioinformatics. Same as ENG EC 724 and ENG SE7 24. Students may not receive credits for both.
  • ENG ME 725: Queueing Systems
    Performance modeling using queueing networks, analysis of product form and non-product form networks, numerical methods for performance evaluation, approximate models of queueing systems, optimal design and control of queueing networks. Applications from manufacturing systems, computer systems and communication networks. Same as ENG EC 725 and ENG SE 725. Students may not receive credits for both.
  • ENG ME 726: Fundamentals of Biomaterials
    Provides the chemistry and engineering skills needed to solve challenges in the biomaterials and tissue engineering area, concentrating on the fundamental principles in biomedical engineering, material science, and chemistry. Covers the structure and properties of hard materials (ceramics and metals) and soft materials (polymers and hydro-gels). Same as ENG BE 526, ENG BE 726,ENG MS 726. Students may not receive credit for both.
  • ENG ME 727: Principles and Applications of Tissues
    Provides the chemistry and engineering skills needed to solve challenges in the biomaterials and tissue engineering area, concentrating on cell-biomaterial interactions, soft tissue mechanics and specific research topics. Students will write a NIH-style grant proposal on a specific research topic. Note that the laboratory portion is not offered in ENG ME 727. Same as ENG BE 527, ENG BE 727, ENG ME 727, ENG MS 727. Students may not receive credit for both.
  • ENG ME 733: Discrete Event and Hybrid Systems
    Review of system theory fundamentals distinguishing between time-driven and event-driven dynamics. Modeling of Discrete Event and Hybrid Systems; Automata, Hybrid Automata, Petri Nets, basic queueing models, and stochastic flow models. Monte Carlo computer simulation: basic structure and output analysis. Analysis, control, and optimization techniques based on Markov Decision Process theory with applications to scheduling, resource allocation, and games of chance. Perturbation Analysis and Rapid Learning methods with applications to communication networks, manufacturing systems, and command-control. Same as ENG EC 733 and ENG SE 733. Students may not receive credits for both.
  • ENG ME 734: Hybrid Systems
    The course offers a detailed introduction to hybrid systems, which are dynamical systems combining continuous dynamics (modeled by differential equations) with discrete dynamics (modeled by automata). The covered topics include modeling, simulation, stability analysis, verification, and control of such systems. The course contains several applications from both natural and manmade environments, ranging from gene networks in biology, to networked embedded systems in avionics and automotive controls, and to motion planning and control in robotics. Same as ENG ME 734 and ENG SE 734. Students may not receive credits for both.
  • ENG ME 740: Vision, Robotics, and Planning
    Methodologies required for constructing and operating intelligent mechanisms. Comprehensive introduction to robot kinematics for motion planning. Dynamics and control of mechanical systems. Formal treatment of differential relationships for understanding the control of forces and torques at the end effector. Discussion of robot vision and sensing and advanced topics in robot mechanics, including elastic effects and kinematic redundancy. Same as ENG SE 740. Students may not receive credits for both.
  • ENG ME 762: Nonlinear Systems and Control
    Introduction to the theory and design methods of non-linear control systems. Application to robotics, vibration and noise control, fluid control, manufacturing processes, and biomedical systems. Mathematical methods based on the theory of differentiable manifolds; non-linear control techniques include feedback linearization, back-stepping, forwarding, and sliding mode control. Additional course topics will include controllability and observability, Lyapunov stability and its applications, limit cycles, input-output stability, zero dynamics, center manifold theory, perturbation theory, and averaging. Same as ENG SE 762. Students may not receive credits for both.
  • ENG ME 766: Advanced Scheduling Models and Methods
    Emphasizes basic methodological tools and recent advances for the solution of scheduling problems in both deterministic and stochastic settings. Models considered include classical scheduling models, DEDS, neural nets, queueing models, flow control models, and linear programming models. Methods of control and analysis include optimal control, dynamic programming, fuzzy control, adaptive control, hierarchical control, genetic algorithms, simulated annealing, Lagrangian relaxation, and heavy traffic approximations. Examples and case studies focus on applications from manufacturing systems, computer and communication networks, and transportation systems. Same as ENG SE 766. Students may not receive credits for both.

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