As a discipline, mechanical engineering encompasses concepts and technologies with the power to transform the futures of organizations and industries. The curriculum in the online Master of Science in Mechanical Engineering program prepares engineers to lead those changes by covering a variety of fields and topics including fluid mechanics, energy, dynamics and control, robotics, additive manufacturing, biomechanics, autonomous vehicles, and thermodynamics.
In this rigorous and mathematically intensive online curriculum, engineers apply analytical methods to complex problems and identify ways to improve industrial processes. Online students may prepare for the quantitative demands of the rest of the program by first completing ME 800 Mechanical Engineering Analysis.
8 Focus Areas
Specialize in high-demand areas of mechanical engineering roles with one of eight focus areas.
Choose from the following tracks:
Advanced Manufacturing
Aerospace
Automotive
Computational Modeling
Controls
Energy
Mechanics, Dynamics, and Manufacturing
Thermal Fluids Science and Engineering
Explore our full list of course descriptions and other curriculum information below.
Inside the Curriculum
Learn about the degree plan, specialization options and how the coursework can benefit your career. Watch the program overview now.
Online M.S. in Mechanical Engineering Program Requirements
Total credit requirement: 30 credits
A maximum of 9 credits at the 400 level
A minimum of 21 credits at the 800 level or above
A maximum of 4 independent credits (total from ME 490 and/or ME 990)
A maximum of half (15 credits) of course credits outside of Mechanical Engineering
Online Mechanical Engineering students must also complete one course from each of the following three areas:
“In online ME820: Continuum Mechanics, students get a fundamental understanding of vector and tensor analysis as applied to solid and fluid mechanics, allowing for a more in-depth and accurate interpretation of mechanical design and material characterization. To overcome the limitations of an asynchronous online format, regular and extra Zoom sessions were provided to assist students’ ongoing learning and engagement. In addition, thorough feedback on assignments, quizzes, and tests was supplied to assist students in identifying and correcting errors, so strengthening their mathematical reasoning and mechanical analysis skills.” Seungik Baek Associate Professor
In-Demand Tracks
Note: Class schedules may be subject to change depending on enrollment and instructor availability.
Advanced Manufacturing
Merge foundational mechanical engineering analysis with modern manufacturing methodologies. It is designed for engineers seeking to optimize processes, improve material performance and guarantee product integrity across complex, next-generation manufacturing systems.
Courses include:
ME 821 Linear Elasticity
ME 860 Theory of Vibrations
ME 874 Analysis of Metal Forming and Manufacturing Processes
Aerospace
Study the rigorous analysis, design and computational modeling of advanced flight vehicles and thermal systems. The comprehensive program provides mastery across the core pillars of mechanical analysis — fluids, thermodynamics and solids – with a specialized focus on high performance aerospace applications.
Courses include:
ME 810 Advanced Classical Thermodynamics
ME 830 Fluid Mechanics
ME 851 Linear Systems and Controls
Automotive
Gain the specialized skills needed to tackle the challenges of future mobility – including powertrain optimization, structural durability and the design of autonomous features.
Courses include:
ME 819 Combustion
ME 851 Linear Systems and Controls
ME 860 Theory of Vibrations
Computational Modeling
Develop advanced computational literacy and multidisciplinary skills required to model, simulate and optimize complex physical systems. Graduates are prepared to lead simulation efforts in aerospace automotive, energy and biomedical fields.
Courses include:
ME 491 Machine Learning for Mechanical Engineering
ME 872 Finite Element Method
ME 840 Computational Fluid Dynamics and Heat Transfer
Controls
Learn the specialized theory and computational tools to develop stable, robust and highly efficient control solutions for robotics, aerospace, automotive and complex manufacturing applications.
Courses include:
ME 851 Linear Systems and Controls
ECE 818 Robotics
ME 859 Nonlinear Control
Energy
Hone analytical and design skills necessary to develop, optimize and manage the next generation of efficient, low-carbon energy systems, spanning renewables, power generation and industrial sustainability.
Courses include:
ME 810 Advanced Classic Thermodynamics
ME 417 Design of Energy Systems
ME 830 Fluid Mechanics
Mechanics, Dynamics, and Manufacturing
Deepen your understanding of forces and motion while expanding your practical skills in mechanical engineering. You’ll build career-ready expertise through immersive design projects and gain proficiency in mechanics and manufacturing.
Courses include:
Continuum Mechanics
Fracture Mechanics and Fatigue
Linear Elasticity
Thermal Fluids Science and Engineering
With this focus area, you’ll prepare to address complex engineering challenges that relate to heat transfer, thermodynamics and fluid mechanics. You’ll also deepen your understanding of probability and statistics to improve your data analysis skills.
Note: Not all courses are available every semester. Contact an Enrollment Specialist for more information on course availability and to discuss your desired academic plan.
Power semiconductor devices, circuits, control, and applications. Converter and inverter analysis and design, DSP (Digital Signal Processor) control and implementation. Automotive and utility applications.
Theory and application of finite difference and finite volume methods to selected fluid mechanics and heat transfer problems developed based on Euler and Navier-Stokes equations. Application of commercial software to computational fluid dynamics problems.
This course has been particularly designed to serve as an exciting transition and advancement of ME 391: Engineering Analysis to data-driven mechanical engineering using machine learning with emphasis on Python coding. Therefore, ME 491: Machine Learning for Mechanical Engineers will be a suitable fusion of the theory and practice of machine learning for the purpose of broadening students’ capabilities in targeting data-driven engineering problems through the following two distinguished parts:
Part I: The first part provides a transition from engineering analysis to data-driven modeling by introducing computational linear algebra, data decomposition techniques, and transform methods applied to complex mechanical engineering problems where analytical solutions are limited.
Part II: The second part focuses on statistical and machine learning methods, including regression, classification, clustering, and neural networks, with hands-on applications to thermo-fluids, dynamical systems, control, and solid mechanics.
Use of analytical methods of mathematics in engineering applications. Applications of partial differential equations to thermal-fluid and vibration problems, vector calculus and tensor analysis in fluid and solid mechanics, and analytical function theory in mechanics.
Mathematical tools of continuum mechanics, stress principles, kinematics of deformation and motion, fundamental laws and equations. Applications in linear elasticity and classical fluids.
Fundamentals of isotropic linear elasticity. Solution of plane elasticity problems. St. Venant bending and torsion. Singular solutions. Basic three-dimensional solutions.
Fundamentals of isotropic linear elasticity. Brittle and ductile fracture. Elastic stress fields near cracks. Elastic-plastic analysis of crack extension. Plastic instability. Cyclic crack propagation. Models of cyclic deformation and fatigue failure. Environmental effects. Case studies. Fracture behavior of thin films.
Integral and differential conservation laws, Navier-Stokes’ equations, and exact solutions. Laminar boundary layer theory, similarity solutions, and approximate methods. Thermal effects and instability phenomena.
Theory and application of finite difference and finite volume methods to selected fluid mechanics and heat transfer models including the full potential flow model, the systems of Euler and Navier-Stokes equations, and turbulence. Grid generation techniques.
State models and their stability, controllability, and observability properties. Finding minimal realizations of transfer functions. Design of state and output feedback controllers. Design of state observers. LQ regulator and the Kalman filter. Time-varying systems.
Second-order systems and fundamental properties of solutions. Lyapunov stability, input-output stability, passivity, absolute stability, and linearization. Design of feedback controllers using integral control, feedback linearization, sliding mode control, Lyapunov redesign, passivity-based control, and recursive methods. Applications to electrical and mechanical systems.
Discrete systems and continua. Analytical mechanics. Variational principles. Modal analysis. Function spaces. Eigenfunction expansions. Integral transforms. Stability. Approximations. Perturbations.
Dynamics of systems of particles and rigid bodies. Energy and momentum principles. Lagrangian and Hamiltonian methods. Euler angles. Applications in system dynamics and vibrations.
Review of fundamental knowledge in mechanics, materials and numerical analysis. Modeling, simulation and analysis of metal forming and manufacturing processes.
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