Academics
Topics include search algorithms, game playing, constraints satisfaction, meta-heuristics, evolutionary computing methods, swarm intelligence, ant-colony algorithms, particle swarm methods, adaptive and learning algorithms. The course details level of co-operation between algorithms and variations of algorithms suitable for solving continous and discrete problems that arise in engineering applications
Topics include search algorithms, game playing, constraints satisfaction, meta-heuristics, evolutionary computing methods, swarm intelligence, ant-colony algorithms, particle swarm methods, adaptive and learning algorithms. The course details level of co-operation between algorithms and variations of algorithms suitable for solving continous and discrete problems that arise in engineering applications
Model-based prediction and classification. Concepts in machine learning, supervised and unsupervised learning, artificial neural networks, deep learning, feature extraction, feature selection, dimensionality reduction, classification and clustering, support vector machines. Approximate reasoning based on fuzzy set theory. Performance metrics to assess the validity of produced models. Multiple examples and case studies such as autonomous driving, intelligent manufacturing, natural language understanding, speech recognition, computer vision, stock market prediction, disease early detection and diagnosis.
Dynamic system modelling: linear, nonlinear, state-space, sample data systems, computer simulation, system identification. Discrete system stability and dynamic performance. Nonlinear system analysis, limit cycles. Digital control system design: emulation methods, z-domain, frequency domain, pole placement. Implementation of digital controllers. Laboratory projects in computer control of mechatronic and other systems.
Physical properties of fluids and fundamental concepts in fluid mechanics. Hydrostatics. Conservation laws for mass, momentum and energy. Flow similarity and dimensional analysis as applied to engineering problems in fluid mechanics. Laminar and turbulent flow. Engineering applications such as flow measurement, flow in pipes and fluid forces on moving bodies.
Integrated design of mechanical motion transmission systems: gearing, couplings, bearings, power screws, fasteners, and their integration; sensing and measurement of mechanical motion; specification and selection of motors and electromechanical actuators; analysis and design of controllers for motion transmission systems; case studies.
Feedback control design and analysis for linear dynamic systems with emphasis on mechanical engineering applications; transient and frequency response; stability; system performance; control modes; state space techniques; Introduction to digital control systems.
Most of the term is devoted to a significant design project in which student groups work independently and competitively, applying the design process to a project goal set by the faculty coordinator. The design project typically includes construction of an electro-mechanical prototype, and part of the course grade may depend on the performance of the prototype in a competitive test. (Our group placed top 5)
Review of Vectors and Vector Operations; 3-D Analytic Geometry and Space Curves; Multivariable Calculus, including Partial Differentiation, Total Differential, Chain Rule, Directional Derivative, Gradient Operator, Maxima and Minima; Multiple Integrals - Surface Area, Volume and Moments of Inertia; Line and Surface Integrals; Vector Theorems; Complex Analysis including Limits, Analytic Functions, Complex Line Integral, Cauchy's Integral Formula; Fourier Series (real and complex) and Fourier Integrals.
Review of Vectors and Vector Operations; 3-D Analytic Geometry and Space Curves; Multivariable Calculus, including Partial Differentiation, Total Differential, Chain Rule, Directional Derivative, Gradient Operator, Maxima and Minima; Multiple Integrals - Surface Area, Volume and Moments of Inertia; Line and Surface Integrals; Vector Theorems; Complex Analysis including Limits, Analytic Functions, Complex Line Integral, Cauchy's Integral Formula; Fourier Series (real and complex) and Fourier Integrals.
Number Systems and Machine Errors; Roots of Non-Linear Equations; Matrix Calculations; Eigenvalue and Eigenvector Calculations; Interpolation and Approximation; Numerical Integration and Solution of ODE's (linear and non-linear) and systems of ODEs; Calculation of Series; Solution Methods for PDE's; Use of numeric and symbolic computing tools.
Input-output relationships, transfer functions and frequency response of linear systems; operational amplifier circuits using feedback, diodes, analog signal detection, conditioning and conversion systems; transducers and sensors, difference and instrumentation amplifiers, and active filters.
Introduction to computer organization, basic real-time concepts, process management, interprocess communication and synchronization, memory management, resource management, interrupt handling, concurrent programming, file systems.
Macroscopic approach to energy analysis. Energy transfer as work and heat, and the First Law of thermodynamics. Properties and states of simple substances. Control-mass and control-volume analysis. The essence of entropy, and the Second Law of thermodynamics. The Carnot cycle and its implications for practical cyclic devices. Introduction to heat transfer by conduction, convection, and radiation. Basic formulation and solution of steady and transient problems. Issues relevant to the cooling of electrical devices.
Review of circuit analysis & basic electromagnetic theory. Power electronics: power electronics circuits, H bridges, PWM control, interfacing, power amplifiers. DC servo & stepper motors, AC synchronous & induction motors. Transformers. Introduction to typical speed and torque control techniques of motors
Principles of the geometry and motion in linkages and mechanisms. Computer-aided kinematic and kinetic analysis of mechanisms. Synthesis of mechanisms. Static failure and yield criteria in ductile and brittle materials. Fatigue failure criteria due to fluctuating stresses. Shaft design under static and fluctuating loads.
Synchronization and data flow; interfacing to sensors and actuators; microprocessor system architecture, parallel, serial, and analog interfacing; buses; direct memory access (DMA); interfacing considerations.
An introduction to mechanical response of materials and stress-strain relationships. Behaviour of members in stresses and strain with corresponding loading types. A cummulative project of this course was designing, prototyping, and analyzing a truss given several constraints with the goal of maximizing the ratio of mass loaded to mass of truss. Tools used include Solidworks, AutoCAD, Lasercutter, powertools, etc.
Computer organization, basic real-time concepts, process management, interprocess communication and synchronization, memory management, resource management, interrupt handling, concurrent programming, file systems.
Circuit theory; input-output relationships, transfer functions and frequency response of linear systems; operational amplifier circuits using negative or positive feedback;operational amplifier circuits using diodes; analog signal detection, conditioning and conversion systems; transducers and sensors, difference and instrumentation amplifiers, active filters.
Number systems, logic gates, Boolean algebra. Karnaugh maps and combinational logic design. Implementation of combinational logic circuits on Field Programmable Gate Arrays (FPGA) boards. Sequential logic and state machines. Programmable Logic Controllers (PLCs) and PLC programming using ladder logic and statement list. Microcomputer structure and operation, I/O, and interfacing and interrupts. Assembly language programming. Laboratory work includes microcomputer and PLC programming.
This course provided deep insight into software design Data Structures, abstract data types, recursive, and iterative Algorithms, including sorting, searching, and hashing. Labs involved using complex data structures and algorithms for solving real world problems.
This course detailed the fundamental principles of material properties, such as the relationships between macroscopic material properties and microscopic causes. Including lab work with various materials to identify said properties using a variety of testing equipment used in industry to perform metallurgic analysis.
This course was an introduction to electronic digital computers, and the basics of programming in C++ and RobotC. Topics ranged from pointer basics and polymorphism.
This course discussed Basic electromagnetic theory, first and second order circuits, physically building and analyizng AC/DC circuits; elements; first-order transient response and AC/DC circuit analysis. Labs included using a variety of tools to test and measure the circuits built. The course gave an insight into solving circuits through rudimentary processes.
This is a thorough statistics course that describes the fundamentals of measurement methods and analysis. There was an end of course project that involved creating an intricate device/system to take measurements of various measurands.
This math course develops methods for solving several types of ODE's through a plethura of methods. Example problems including Laplace transforms of second order circuits. This course entailed a project that required handwritten methods and MATLAB for graphical representations of the final solutions.
This course detailed design process, project planning, as well as an indepth look into GD&T through 2D and 3D Software designs such as AutoCAD and Solidworks
Kinematics of particles, rectilinear and curvilinear motion. Kinetics of particles, application to space mechanics. Energy and momentum methods. Systems of particles. Kinematics and kinetics of rigid bodies; planar motion. Vibrations.
Multivariable Calculus, including Partial Differentiation, Total Differential, Chain Rule, Directional Derivative, Gradient Operator, Maxima and Minima; Multiple Integrals - Surface Area, Volume and Moments of Inertia; Line and Surface Integrals; Vector Theorems; Complex Analysis including Limits, Analytic Functions, Complex Line Integral, Cauchy's Integral Formula; Fourier Series (real and complex) and Fourier Integrals.
Number Systems and Machine Errors; Roots of Non-Linear Equations; Matrix Calculations; Eigenvalue and Eigenvector Calculations; Interpolation and Approximation; Numerical Integration and Solution of ODE's (linear and non-linear) and systems of ODEs; Calculation of Series; Solution Methods for PDE's; Use of numeric and symbolic computing tools.