Mechanical engineering programs massachusetts

State observers, Kalman filters. Basic optimization tools. Positive systems. Emphasizes applications to physical systems. Slotine, K. Youcef-Toumi, N. Same subject as 9. Introduction to nonlinear control and estimation in physical and biological systems. Nonlinear stability theory, Lyapunov analysis, Barbalat's lemma. Feedback linearization, differential flatness, internal dynamics. Sliding surfaces. Adaptive nonlinear control and estimation.

Multiresolution bases, nonlinear system identification. Contraction analysis, differential stability theory. Nonlinear observers. Asynchronous distributed computation and learning. Concurrent synchronization, polyrhythms. Monotone nonlinear systems. Emphasizes application to physical systems robots, aircraft, spacecraft, underwater vehicles, reaction-diffusion processes, machine vision, oscillators, internet , machine learning, computational neuroscience, and systems biology.

Includes term projects. Lays the foundation of adaptive control, and investigates its interconnections with machine learning. Explores fundamental principles of adaptive control, including parameter estimation, recursive algorithms, stability properties, and conditions for convergence. Studies their relationship with machine learning, including the minimization of a performance error and fast convergence.

Discusses robustness and regularization in both fields. Derives conditions of learning and implications of imperfect learning. Examines the trade-off between stability and learning.

Focuses throughout the term on dynamic systems and on problems where real-time control is needed. Uses examples from aerospace, propulsion, automotive, and energy systems to elucidate the underlying concepts.

Maneuvering motions of surface and underwater vehicles. Derivation of equations of motion, hydrodynamic coefficients. Memory effects. Linear and nonlinear forms of the equations of motion. Control surfaces modeling and design. Engine, propulsor, and transmission systems modeling and simulation during maneuvering. Stability of motion. Principles of multivariable automatic control. Optimal control, Kalman filtering, loop transfer recovery. Term project: applications chosen from autopilots for surface vehicles; towing in open seas; remotely operated vehicles.

Introduces fundamental concepts and encourages open-ended exploration of the increasingly topical intersection between artificial intelligence and the physical sciences. Energy and information, and their respective optimality conditions are used to define supervised and unsupervised learning algorithms; as well as ordinary and partial differential equations.

Subsequently, physical systems with complex constitutive relationships are drawn from elasticity, biophysics, fluid mechanics, hydrodynamics, acoustics, and electromagnetics to illustrate how machine learning-inspired optimization can approximate solutions to forward and inverse problems in these domains. Provides a broad theoretical basis for system identification, estimation, and learning. Least squares estimation and its convergence properties, Kalman filter and extended Kalman filter, noise dynamics and system representation, function approximation theory, neural nets, radial basis functions, wavelets, Volterra expansions, informative data sets, persistent excitation, asymptotic variance, central limit theorems, model structure selection, system order estimate, maximum likelihood, unbiased estimates, Cramer-Rao lower bound, Kullback-Leibler information distance, Akaike's information criterion, experiment design, and model validation.

Building on core material in 6. Uses energy and information, and their respective optimality conditions, to define supervised and unsupervised learning algorithms as well as ordinary and partial differential equations.

Students cannot receive credit without simultaneous completion of 6. Introduction to robotics and learning in machines. Kinematics and dynamics of rigid body systems. Adaptive control, system identification, sparse representations. Force control, adaptive visual servoing. Task planning, teleoperation, imitation learning.

Underactuated systems, approximate optimization and control. Dynamics of learning and optimization in networks. Elements of biological planning and control. Motor primitives, entrainment, active sensing, binding models. Term projects. Prereq: 6. Theory and application of probabilistic techniques for autonomous mobile robotics.

Topics include probabilistic state estimation and decision making for mobile robots; stochastic representations of the environment; dynamic models and sensor models for mobile robots; algorithms for mapping and localization; planning and control in the presence of uncertainty; cooperative operation of multiple mobile robots; mobile sensor networks; application to autonomous marine underwater and floating , ground, and air vehicles.

A comprehensive introduction to digital control system design, reinforced with hands-on laboratory experiences. Major topics include discrete-time system theory and analytical tools; design of digital control systems via approximation from continuous time; direct discrete-time design; loop-shaping design for performance and robustness; state-space design; observers and state-feedback; quantization and other nonlinear effects; implementation issues.

Laboratory experiences and design projects connect theory with practice. Provides a review of biology concepts, regulation mechanisms, and models. Covers basic enabling technologies, engineering principles for designing biological functions, modular design techniques, and design limitations. Presents a quantitative description of how biomechanical and neural factors interact in human sensory-motor behavior.

Students survey recent literature on how motor behavior is controlled, comparing biological and robotic approaches to similar tasks. Topics may include a review of relevant neural, muscular and skeletal physiology, neural feedback and "equilibrium-point" theories, co-contraction strategies, impedance control, kinematic redundancy, optimization, intermittency, contact tasks and tool use.

Prereq: 1. The fundamentals of fluid mechanics are developed in the context of naval architecture and ocean science and engineering. Transport theorem and conservation principles. Navier-Stokes' equation. Ideal and potential flows. Vorticity and Kelvin's theorem. Hydrodynamic forces in potential flow, D'Alembert's paradox, added-mass, slender-body theory. Viscous-fluid flow, laminar and turbulent boundary layers.

Model testing, scaling laws. Linearized theory of lifting surfaces. Experimental project in the towing tank or propeller tunnel.

Design tools for analysis of linear systems and random processes related to ocean vehicles; description of ocean environment including random waves, ocean wave spectra and their selection; short-term and long-term wave statistics; and ocean currents.

Advanced hydrodynamics for design of ocean vehicles and offshore structures, including wave forces on towed and moored structures; inertia vs. Design exercises in application of principles. Laboratory exercises in seakeeping and VIV at model scale. Reviews the theory and design of hydrofoil sections; lifting and thickness problems for sub-cavitating sections and unsteady flow problems.

Covers lifting line and lifting surface theory with applications to hydrofoil craft, rudder, control surface, propeller and wind turbine rotor design. Topics include propeller lifting line and lifting surface theory; wake adapted propellers, steady and unsteady propeller thrust and torque; waterjets; performance analysis and design of wind turbine rotors. Presents numerical principles of vortex lattice and lifting surface panel methods.

Projects illustrate the development of theoretical and computational methods for lifting, propulsion and wind turbine applications. Surface wave theory, conservation laws and boundary conditions, properties of regular surface waves and random ocean waves. Linearized theory of floating body dynamics, kinematic and dynamic free surface conditions, body boundary conditions.

Simple harmonic motions. Diffraction and radiation problems, added mass and damping matrices. General reciprocity identities on diffraction and radiation.

Ship wave resistance theory, Kelvin wake physics, ship seakeeping in regular and random waves. Discusses point wave energy absorbers, beam sea and head-sea devises, oscillating water column device and Well's turbine. Discusses offshore floating energy systems and their interaction with ambient waves, current and wind, including oil and gas platforms, liquefied natural gas LNG vessels and floating wind turbines.

Homework drawn from real-world applications. Survey of principal concepts and methods of fluid dynamics. Mass conservation, momentum, and energy equations for continua.

Navier-Stokes equation for viscous flows. Similarity and dimensional analysis. Lubrication theory. Boundary layers and separation. Circulation and vorticity theorems. Potential flow. Introduction to turbulence. Lift and drag.

Surface tension and surface tension driven flows. Ghoniem, A. Hosoi, G. McKinley, A. Discusses a range of topics and advanced problem-solving techniques. Sample topics include brief review of basic laws of fluid motion, scaling and approximations, creeping flows, boundary layers in high-speed flows, steady and transient, similarity method of solution, buoyancy-driven convection in porous media, dispersion in steady or oscillatory flows, physics and mathematics of linearized instability, effects of shear and stratification.

Akylas, G. McKinley, R. Fundamentals and modeling of reacting gas dynamics and combustion using analytical and numerical methods.

Conservation equations of reacting flows. Multi-species transport, chemical thermodynamics and chemical kinetics. Non-equilibrium flow. Detonation and reacting boundary layers. Ignition, flammability, and extinction. Premixed and diffusion flames. Combustion instabilities. Supersonic combustion. Turbulent combustion. Liquid and solid burning. Fire, safety, and environmental impact. Applications to power and propulsion. Direct and iterative methods for linear systems. Finite differences for elliptic, parabolic and hyperbolic equations.

Fourier decomposition, error analysis and stability. High-order and compact finite-differences. Finite volume methods. Time marching methods. Navier-Stokes solvers. Grid generation. Finite volumes on complex geometries. Finite element methods.

Spectral methods. Boundary element and panel methods. Turbulent flows. Boundary layers. Lagrangian Coherent Structures. Includes a final research project. Physical phenomena in polymeric liquids undergoing deformation and flow. Kinematics and material functions for complex fluids; techniques of viscometry, rheometry; and linear viscoelastic measurements for polymeric fluids.

Generalized Newtonian fluids. Continuum mechnanics, frame invariance, and convected derivatives for finite strain viscoelasticity. Differential and integral constitutive equations for viscoelastic fluids.

Analytical solutions to isothermal and non-isothermal flow problems; the roles of non-Newtonian viscosity, linear viscoelasticity, normal stresses, elastic recoil, stress relaxation in processing flows. Introduction to molecular theories for dynamics of polymeric fluids. Extensive class project and presentation required instead of a final exam. Presents the fundamentals of molecular modeling in engineering in the context of nanoscale mechanical engineering applications.

Statistical mechanics and its connection to engineering thermodynamics. Molecular origin and limitations of macroscopic descriptions and constitutive relations for equilibrium and non-equilibrium behavior.

Introduction to molecular simulation, solid-state physics and electrokinetic phenomena. Discusses molecular approaches to modern nanoscale engineering problems. Graduate students are required to complete additional assignments with stronger analytical content. Provides an introduction to microsystem design. Covers material properties, microfabrication technologies, structural behavior, sensing methods, electromechanical actuation, thermal actuation and control, multi-domain modeling, noise, and microsystem packaging.

Applies microsystem modeling, and manufacturing principles to the design and analysis a variety of microscale sensors and actuators e. Emphasizes modeling and simulation in the design process. Prereq: Permission of instructor G Fall units. General foundations of thermodynamics from an entropy point of view, entropy generation and transfer in complex systems.

Definitions of work, energy, stable equilibrium, available energy, entropy, thermodynamic potential, and interactions other than work nonwork, heat, mass transfer.

Applications to properties of materials, bulk flow, energy conversion, chemical equilibrium, combustion, and industrial manufacturing. Introduces the fundamental science and technology of desalinating water to overcome water scarcity and ensure sustainable water supplies.

Covers basic water chemistry, flash evaporation, reverse osmosis and membrane engineering, electrodialysis, nanofiltration, solar desalination, energy efficiency of desalination systems, fouling and scaling, environmental impacts, and economics of desalination systems.

Open to upper-class undergraduates. Covers conduction governing equations and boundary conditions, steady and unsteady heat transfer, resistance concept ; laminar and turbulent convection forced-convection and natural-convection boundary layers, external flows ; radiation blackbody and graybody exchange, spectral and solar radiation ; coupled conduction, convection, radiation problems; synthesis of analytical, computational, and experimental techniques; and mass transfer at low rates, evaporation.

Lienhard, A. Patera, E. Same subject as 4. Provides instruction on how to model thermal transport processes in typical engineering systems such as those found in manufacturing, machinery, and energy technologies. Successive modules cover basic modeling tactics for particular modes of transport, including steady and unsteady heat conduction, convection, multiphase flow processes, and thermal radiation. Includes a creative design project executed by the students. Advanced treatment of fundamental aspects of heat and mass transport.

Covers topics such as diffusion kinetics, conservation laws, laminar and turbulent convection, mass transfer including phase change or heterogeneous reactions, and basic thermal radiation.

Problems and examples include theory and applications drawn from a spectrum of engineering design and manufacturing problems. Parallel treatments of photons, electrons, phonons, and molecules as energy carriers; aiming at a fundamental understanding of descriptive tools for energy and heat transport processes, from nanoscale to macroscale.

Topics include energy levels; statistical behavior and internal energy; energy transport in the forms of waves and particles; scattering and heat generation processes; Boltzmann equation and derivation of classical laws; and deviation from classical laws at nanoscale and their appropriate descriptions. Applications in nanotechnology and microtechnology. Principles of thermal radiation and their application to engineering heat and photon transfer problems.

Quantum and classical models of radiative properties of materials, electromagnetic wave theory for thermal radiation, radiative transfer in absorbing, emitting, and scattering media, and coherent laser radiation. Applications cover laser-material interactions, imaging, infrared instrumentation, global warming, semiconductor manufacturing, combustion, furnaces, and high temperature processing.

Fundamentals of thermodynamics, chemistry, and transport applied to energy systems. Analysis of energy conversion and storage in thermal, mechanical, chemical, and electrochemical processes in power and transportation systems, with emphasis on efficiency, performance, and environmental impact. Applications to fuel reforming and alternative fuels, hydrogen, fuel cells and batteries, combustion, catalysis, combined and hybrid power cycles using fossil, nuclear and renewable resources. CO 2 separation and capture.

Biomass energy. Introduces the fundamentals of power system structure, operation and control. Emphasizes the challenges and opportunities for integration of new technologies: photovoltaic, wind, electric storage, demand response, synchrophasor measurements.

Introduces the basics of power system modeling and analysis. Presents the basic phenomena of voltage and frequency stability as well technological and regulatory constraints on system operation. Describes both the common and emerging automatic control systems and operator decision-making policies. Relies on a combination of traditional lectures, homework assignments, and group projects.

Fundamentals of how the design and operation of internal combustion engines affect their performance, efficiency, fuel requirements, and environmental impact.

Study of fluid flow, thermodynamics, combustion, heat transfer and friction phenomena, and fuel properties, relevant to engine power, efficiency, and emissions. Examination of design features and operating characteristics of different types of internal combustion engines: spark-ignition, diesel, stratified-charge, and mixed-cycle engines. Engine Laboratory project.

For graduate and senior undergraduate students. Selection and evaluation of commercial and naval ship power and propulsion systems. Analysis of propulsors, prime mover thermodynamic cycles, propeller-engine matching. Propeller selection, waterjet analysis, review of alternative propulsors; thermodynamic analyses of Rankine, Brayton, Diesel, and Combined cycles, reduction gears and integrated electric drive.

Battery operated vehicles, fuel cells. Term project requires analysis of alternatives in propulsion plant design for given physical, performance, and economic constraints. Graduate students complete different assignments and exams. Harbour, M. Triantafyllou, R. Analysis of energy conversion and storage in thermal, mechanical, chemical, and electrochemical processes in power and transportation systems, with emphasis on efficiency, performance and environmental impact.

Meets with 2. Fundamental concepts, tools, and applications in electrochemical science and engineering. Introduces thermodynamics, kinetics and transport of electrochemical reactions. Describes how materials structure and properties affect electrochemical behavior of particular applications, for instance in lithium rechargeable batteries, electrochemical capacitors, fuel cells, photo electrochemical cells, and electrolytic cells. Discusses state-of-the-art electrochemical energy technologies for portable electronic devices, hybrid and plug-in vehicles, electrical vehicles.

Theoretical and experimental exploration of electrochemical measurement techniques in cell testing, and in bulk and interfacial transport measurements electronic and ionic resistivity and charge transfer cross the electrode-electrolyte interface. Fundamentals of photoelectric conversion: charge excitation, conduction, separation, and collection. Studies commercial and emerging photovoltaic technologies. Cross-cutting themes include conversion efficiencies, loss mechanisms, characterization, manufacturing, systems, reliability, life-cycle analysis, and risk analysis.

Photovoltaic technology evolution in the context of markets, policies, society, and environment. Graduate students complete additional work. Limited to juniors and seniors. Same subject as EC. See description under subject EC. Enrollment limited by lottery; must attend first class session. Limited to 20; preference to students who have taken EC.

Introduces the fundamentals of machine tools use and fabrication techniques. Students work with a variety of machine tools including the bandsaw, milling machine, and lathe. Mechanical Engineering students are advised to take this subject in the first IAP after declaring their major. Preference to Course 2 majors and minors. Institute LAB. Experimental techniques for observation and measurement of physical variables such as force, strain, temperature, flow rate, and acceleration. Emphasizes principles of transduction, measurement circuitry, MEMS sensors, Fourier transforms, linear and nonlinear function fitting, uncertainty analysis, probability density functions and statistics, system identification, electrical impedance analysis and transfer functions, computer-aided experimentation, and technical reporting.

Typical laboratory experiments involve oscilloscopes, electronic circuits including operational amplifiers, thermocouples, strain gauges, digital recorders, lasers, etc. Basic material and lab objectives are developed in lectures. Enrollment limited. Enrollment limited; preference to Course 20 undergraduates. Blainey, S. Manalis, E. Frank, S. Wasserman, J. Bagnall, E.

Boyden, P. Presents concepts, ideas, and enabling tools for nanoengineering through experiential lab modules, which include microfluidics, microelectromechanical systems MEMS , and nanomaterials and nanoimaging tools such as scanning electron microscopy SEM , transmission electron microscopy TEM , and atomic-force microscopy AFM.

This program includes lower-level engineering courses, like Introduction to Mechanical Engineering and Introduction to Materials Science. A Bachelor's degree takes about four years to complete, because it includes credits of coursework. You take many of the same classes as an Associate's degree student, in addition to higher-level courses like Heat Transfer Laboratory and Thermodynamics.

Much of your time may be spent in the lab, learning about different materials and how they work in engineering processes. Master's and doctoral degrees are ideal for you if you want to work in teaching or researching mechanical engineering. A Master's degree takes about two years to complete if you are a full-time student. A PhD takes most students at least five to seven years of full-time study; the length of your program depends on how long it takes you to complete your thesis.

The critter purposely was selected because of its "remarkable engineering and mechanical skill and its habits of industry. The distinguished scholars teaching in the mechanical engineering department are also cutting-edge researchers.

From helping to bring clean water to rural India by designing a solar-powered desalination device to creating a humanoid robot for disaster and rescue missions, they use their knowledge to solve real-world problems. If creative problem-solving energizes you, MIT might be your ideal place. Tufts University offers 3 Mechanical Engineering degree programs. It's a large, private not-for-profit, four-year university in a large suburb. In , 82 Mechanical Engineering students graduated with students earning 53 Bachelor's degrees, 24 Master's degrees, and 5 Doctoral degrees.

Northeastern University offers 3 Mechanical Engineering degree programs. It's a very large, private not-for-profit, four-year university in a large city. Mechanical engineers are problem solvers who help industries tackle important challenges such as developing new power and autonomous systems and advanced composite materials, as well as new methods of enhancing productivity and quality in manufacturing.

The B. Our program emphasizes hands-on experience based in the design-build-test methodology, providing opportunities to build and test your theoretical designs. In addition, you will take relevant courses in the humanities and social sciences. Accredited by ABET , the mechanical engineering program features award-winning researchers and dedicated academics committed to providing students with a high-quality, comprehensive education.

View the requirements. View the Academic Catalog for a complete course listing. Degree Pathways are a semester-by-semester sequence of courses recommended for successful completion of a degree, diploma, credential or certificate from the university. At graduation students should:.