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Examines the core concepts of sustainability for graduate students in the School of Sustainable Energy Engineering (SEE). Principles of sustainability and the role of technology in addressing critical challenges relating to society’s use of energy are discussed. Specific topics will include technologies for low-impact/renewable electrical energy generation, distribution, and utilization in stationary and mobile applications. It is required for students in the SEE MASc program and is optional for students in the SEE PhD program. Prerequisite: Open to SEE MASc students or permission of the Graduate Program Chair. Corequisite: SEE 896 (MASc) or SEE 897 (PhD).

Communication skills, knowledge and strategies to support successful graduate student research in engineering including communicating clearly and concisely with interdisciplinary, technical, and non-technical audiences. Students will learn to identify areas for investigation, propose a writing project, source relevant and reliable literature, use an intentional writing process, address rhetorical issues of audience, purpose and style, and practice constructive, analytical and empowering peer review. A special emphasis will be communicating with policy audiences. Students will practice clear, concise, and impactful professional presentations for interdisciplinary audiences.

Presentation and discussion of current research topics. Includes guest speakers, student presentations, readings, and professional development workshops. A focus is building a community of sustainability scholars while enhancing student well-being. MASc students must enroll in SEE 896 every term in which they are enrolled, until all program requirements have been met. Graded on a satisfactory/unsatisfactory basis.

State-space analysis of finite dimensional continuous and discrete time linear systems. Linear vector spaces, linear operators, normed linear spaces, and inner product spaces. Fundamentals of matrix algebra; generalized inverses, solution of Ax=y and AXB=Y, least square and recursive least square estimation, induced norm and matrix measures, functions of a square matrix, Cayley-Hamilton and Sylvester's theorems, Singular Value Decomposition (SVD) with applications. Analytical representation of linear systems, state-space formulation, solution of the state equation and determination of the system's response. Controllability, observability, duality, canonical forms, and minimal realization concepts. Stability analysis and the Lyapunov's method. Prerequisite: Graduate standing.

The application of theories in probability, random variables and stochastic processes in the analysis and modelling of engineering systems. Topics include: a review of probability and random variables; random deviate generation; convergence of random sequences; random processes; auto correlation and power spectral-density; linear systems with stochastic inputs; mean-square calculus; AR and ARMA models; Markov chains; elementary queuing theory; an introduction to estimation theory. Areas of application include digital communications, speech and image processing, control, radar and Monte Carlo simulations. Prerequisite: Graduate standing.

Processing techniques for continuous and discrete signals with initially unknown or time-varying characteristics. Parameter estimation; Bayes, MAP, maximum likelihood, least squares the Cramer-Rao bound. Linear estimation, prediction, power spectrum estimation, lattice filters. Adaptive filtering by LMS and recursive least squares. Kalman filtering. Eigenmethods for spectral estimation. Implementation issues and numerical methods of computation are considered throughout. Prerequisite: ENSC 802 and 429 or their equivalents.

This course covers the techniques needed to understand and analyse modern communications networks. The main topics are as follow: practical techniques for the design and performance analysis of data communication networks; performance analysis of error control, flow and congestion control, and routing; networks of queues using stochastic and mean value analysis; polling and random access LANs and MANs; wireless networks; broadband integrated services digital networks and asynchronous transfer mode; optical networks. Prerequisite: ENSC 802 or permission of instructor.

Techniques needed to understand and analyze modern data communications networks. Basic architecture of packet networks and their network elements (switches, routers, bridges), and the protocols used to enable transmission of packets through the network. Techniques for collection, characterization, and modeling of traffic in packet networks. Aspects of traffic management, such as call admission control and congestion control algorithms in packet networks and the influence of traffic on network performance. Prerequisite: ENSC 427 or permission of the instructor.

Microelectronic transducer principles, classification, fabrication and application areas. Silicon micromachining and its application to integrated microelectronic sensors and actuators. CMOS compatible micromachining, static, dynamic and kinematic microactuator fabrication. Integrated transducer system design and applications. Students will be required to complete a micromachining project in the microfabrication lab at ENSC. Prerequisite: ENSC 475 and ENSC 495 or permission of instructor.

Scientific and engineering principles of fuel cell systems, including fundamental electrochemistry, applied thermodynamics, and transport phenomena. Types of fuel cells: low temperature and high temperature fuel cell systems and applications. Students are required to complete a project.

Theories, methods, and applications of optimization in support of engineering design. Topics include classic optimization methods, metaheuristics and evolutionary algorithms, Design of Experiments, and metamodel-based design optimization approaches. Students are required to complete a project.

Overview of manufacturing systems: industrial robotics, numerical control and metal cutting, manufacturing system components and definitions, material handling systems, production lines, assembly systems, robotic cell design, cellular manufacturing, flexible manufacturing systems, quality control, and manufacturing support systems. Students are required to complete a project.

Provides insight regarding advanced additive manufacturing technologies in various mechatronic applications. Comprehensive knowledge is presented relevant to advanced 3D printing technologies including direct writing, paste extrusion, and laser direct writing. Topics range from 3D printable material design to application-driven engineering design technology trends including state-of-the-art 3D printed applications. Students will learn the practical perspective of advanced additive manufacturing with various engineering materials: polymers, metals, composites, nano-materials, and biomaterials.

Advanced course on conduction heat and mass transfer. Fundamental elements of heat conduction. Laplace's equation and its applications. Analysis and modelling of engineering systems involving conduction heat transfer. Experimental methods related to conductive heat transfer. Introduction to cooling systems commonly used in microelectronics industry. Recommended: MSE 223 and MSE 321 or their equivalents.

Advanced course on convection heat and mass transfer. Fundamental elements of fluid flow and heat transfer using conservation principles. Analysis and modelling of engineering systems involving convective heat transfer. Experimental methods related to convective heat transfer. Heat/mass transfer and cooling/heating systems commonly used in energy management systems such as microelectronics industry, HVAC systems, fuel cell technologies, and automotive industry. Recommended: MSE 223 and MSE 321 or their equivalents.

Modern engineering materials design for energy system applications. Predictive modelling and design implications applied to energy systems. Advanced theoretical and experimental investigations will be discussed to understand the methodologies for design of materials and machinery to be applied to the energy conversion. Corequisite: SEE 896 or SEE 897. Recommended: SEE 222.

Water usage and global water shortages; principles of membrane separation including microfiltration, ultrafiltration, nanofiltration and reverse osmosis; physico-chemical criteria for separations and membrane materials; basic mass transport in mixed solute systems; polarization and fouling; prediction of membrane performance; operational issues, limitations, energy requirements and system configurations. Corequisite: SEE 896 or SEE 897. Recommended: SEE 224 and SEE 225.

Electrochemical, mechanical and thermal energy storage techniques; integration for stationary and mobile applications; design tradeoffs to understand environmental impacts, cost, reliability, and efficiency. Corequisite: SEE 896 or SEE 897. Recommended: SEE 224 and SEE 230.

Directed Study in Sustainable Energy Engineering. Corequisite: SEE 896 or SEE 897.

Special Topics in Sustainable Energy Engineering. Corequisite: SEE 896 or SEE 897.

Special Topics in Sustainable Energy Engineering. Corequisite: SEE 896 or SEE 897.

Special Topics in Sustainable Energy Engineering. Corequisite: SEE 896 or SEE 897.

The standard techniques of multiple regression analysis, analysis of variance, and analysis of covariance, and their role in experimental research. Prerequisite: Any course in Statistics. Open only to students in departments other than Statistics and Actuarial Science. Students with credit for STAT 302 may not take this course for further credit.

MASc Thesis. Graded on a satisfactory/unsatisfactory basis. Corequisite: SEE 896.