Various production processes use simulation software to shorten the route from the initial design to finished product. Simulation software provides the designer and practicing engineer with a powerful tool in the tasks of improving and optimizing the industrial processes. Expensive trials can be avoided and the quality of the finished product secured from the beginning of production. First, this course will cover the basics of the process simulation used in industrial setting. Subsequently, the course will focus on industrial process simulation software used extensively in foundry industry worldwide. Essential elements of CAD/CAM techniques will be covered. Numerical simulation of the filling and solidification in castings will be presented. Calculation of foundry processes with multiple production cycles will be analyzed. Another course feature will be the graphical presentation of the results on the screen. Limited enrolment.

The unique surface properties and the ability to surface engineer nanocrystalline structures renders these materials to be ideal candidates for use in corrosion, catalysis and energy conversion devices. This course deals with the fabrication of materials suitable for use as protective coatings, and their specific exploitation in fields of hydrogen technologies (electrolysis, storage, and fuel cells) linked to renewables. These new devices are poised to have major impacts on power generation utilities, the automotive sector, and society at large. The differences in observed electrochemical behavior between amorphous, nanocrystalline and polycrystalline solid materials will be discussed in terms of their surface structure and surface chemistry. A major team design project along with demonstrative laboratory exercises constitutes a major portion of this course. Limited Enrolment.

Various synthesis techniques to produce nanostructured materials will be introduced. These include methods involving the vapor phase (physical and chemical vapor deposition, organometallic chemical vapor deposition), the liquid phase (rapid solidification, spark erosion), the solid phase, (mechanical attrition, equal channel deformation) as well techniques producing these structures from solution (electrodeposition, electroless processing, precipitation). Secondary processing techniques to produce final products or devices will also be discussed.

The unique combinations of physical, electrical, magnetic, and thermomechanical properties exhibited by advanced technical ceramics has led to a wide range of applications including automobile exhaust sensors and fuel cells, high speed cutting tool inserts and ball bearings, thermal barrier coatings for turbine engines, and surgical implants. This course examines the crystal and defect structures which determine the electrical and mass transport behaviours and the effects of microstructure on optical, magnetic, dielectric, and thermomechanical properties. The influence of these structure-property relations on the performance of ceramic materials in specific applications such as sensors, solid oxide fuel cells, magnets, and structural components is explored.

Electron quantum wave theory of solid-state materials will be introduced. Quantum phenomena in various materials systems, in particular nano materials, will be discussed. Electronic properties of materials such as charge transport, dielectric properties, optical properties, magnetic properties, and thermal properties will be discussed using appropriate quantum theory. Materials systems to be studied may include metals, semiconductors, organics, polymers, and insulators.

In this course students will be exposed to the applications of machine learning for materials design, including physical metallurgy, catalysis and mechanics of materials. We will begin by conducting a review of statistical and numerical methods, and programming in R and Python. Then, the most important machine learning techniques of relevance to materials science will be described. This will include linear, nonlinear and logistic regression, decision trees, artificial neural networks, deep learning, supervised and unsupervised learning. Thereafter, the students will be provided hands-on experience on analyzing data and apply ML approaches through a set of case studies, pertaining to alloy design, additive manufacturing, and catalyst design. Finally, students will apply these skills through a term project on materials science problem of their interest.

Due to the broad nature of course topics, we encourage students from Chem Eng, MIE, Chemistry, and other departments.

Understanding how different materials fail is a key design consideration in materials science. In this course students will be exposed to the mechanisms leading to the damage and failure of engineering materials, and modeling of failure at atomic and continuum levels. First, we will describe different mechanisms by which various materials fail, including metals, alloys, ceramics, composite materials, and nanomaterials; and the nature of failure – brittle vs. ductile. Then, various approaches to model and analyze damage and failure in materials will be discussed, including finite element-based failure analysis at the macroscale, and molecular dynamics at the atomic scale. Hands-on practice will be provided through practical case studies using softwares. Finally, students will apply these skills through a term project on a materials science problem of their interest.

The one-week intensive course includes additive manufacturing (AM) process fundamentals, material properties, design rules, qualification methods, cost and value analysis, and industrial and consumer applications of AM. Particular emphasis will be placed on AM technologies for metals and other advanced materials (ceramics and composites), and related design principles and part performance. The AM techniques introduced in this course include, but are not limited, to selective laser melting, direct metal deposition, wire arc deposition, cold spray, powder binder jetting, electroplating, fused deposition modeling (FDM) and stereolithography (SLA).

Lab activities (virtual / hands-on) involving both desktop and industrial-grade 3D printers for metals, ceramics and composites, addressing the full workflow from design to characterization. Several interactive case studies which deploy quantitative analysis tools discussed in lecture to solve a real or imagined market or business need. Virtual / in-person visits to local AM startups and an AM equipment provider/integrator. A multidisciplinary team of speakers including industry experts, and special guest speakers (some are U of T Alumni). This course provides students with a comprehensive understanding of AM technology, its applications, and its implications both now and in the future.

The various roles of a practicing engineer in industry and society will be presented through a series of seminars. The lecturers will include practicing engineers from local companies and consulting firms and representatives from professional and technical societies.

The course offers an opportunity to carry out an independent research under the supervision of an academic staff for the students interested in expanding their research capabilities. The students will submit a proposal in the beginning of the course that describes the problem and work plan together with an estimate of the level of effort (hours of work). The grading will be based on a final report and presentation, assessed by a minimum of two faculty members. Students may take this as a half-credit course in the F semester or complement it with the equivalent S semester course for a full credit, in the case of more extensive thesis projects in consultation with the supervising faulty.

The course offers an opportunity to carry out an independent research under the supervision of an academic staff for the students interested in expanding their research capabilities. The students will submit a proposal in the beginning of the course that describes the problem and work plan together with an estimate of the level of effort (hours of work). The grading will be based on a final report and presentation, assessed by a minimum of two faculty members. Students may take this as a half-credit course in the S semester or complement it with the equivalent F semester course for a full credit, in the case of more extensive thesis projects, in consultation with the supervising faulty.

The students, working in small groups complete a project involving design of a materials processing plant, leading to a design report delivered at the conclusion of the course. The topics covered in the lectures and design process include basic materials processing flowsheet for primary processing and recycling of materials, materials and energy balance of individual units and of overall process flowsheets, use of computer software for flowsheet evaluation, translating process flowsheets to resource and utility requirements, energy analysis, capital/operating cost, basics of equipment sizing, operation scheduling, safety and HAZOP, plant layout, and design for sustainability.

This course is designed to provide an integrated approach to composite materials design, and provide a strong foundation for further studies and research on these materials. Topics include: structure, processing, and properties of composite materials; design of fillers reinforcements and matrices reinforcements, reinforcement forms, nanocomposites systems, manufacturing processes, testing and properties, micro and macromechanics modeling of composite systems; and new applications of composites in various sectors.

Mechanics forms the basic background for the understanding of physics. This course on Classical, or Newtonian mechanics, considers the interactions which influence motion. These interactions are described in terms of the concepts of force, momentum and energy. Initially the focus is on the mechanics of a single particle, considering its motion in a particular frame of reference, and transformations between reference frames. Then the dynamics of systems of particles is examined.

The first half of the semester will give an introduction to the basic ideas of classical oscillations and waves. Topics include simple harmonic motion, forced and damped harmonic motion, coupled oscillations, normal modes, the wave equation, travelling waves and reflection and transmission at interfaces. The second half of the semester will first give an introduction to Einstein's special relativity, including evidence for the frame-independence of the speed of light, time dilation, length contraction, causality, and the relativistic connection between energy and momentum. Then we will follow the historical development of quantum mechanics with the photo-electric and Compton effects, the Bohr atom, wave-particle duality, leading to Schrödinger's equation and wave functions with a discussion of their general properties and probabilistic interpretation.

The first half of the semester will continue with the development of quantum mechanics. Topics will include Shrödinger's wave mechanics, tunneling, bound states in potential wells, the quantum oscillator, and atomic spectra. The second half of the semester will give an introduction to the basic ideas of classical statistical mechanics and radiation, with applications to experimental physics. Topics will include Boltzmann's interpretation of entropy, Maxwell-Boltzman statistics, energy equipartition, the perfect gas laws, and blackbody radiation.

Experiments in this course are designed to form a bridge to current experimental research. A wide range of experiments are available using contemporary techniques and equipment. In addition to the standard set of experiments a limited number of research projects are also available. Many of the experiments can be carried out with a focus on instrumentation.

Experiments in this course are designed to form a bridge to current experimental research. A wide range of experiments are available using contemporary techniques and equipment. In addition to the standard set of experiments, a limited number of research projects may be available. This laboratory is a continuation of PHY327H1.

The course is intended to provide an introduction and a very interdisciplinary experience to robotics. The structure of the course is modular and reflects the perception-control-action paradigm of robotics. The course, however, aims for breadth, covering an introduction to the key aspects of general robotic systems, rather than depth, which is available in later more advanced courses. Applications addressed include robotics in space, autonomous terrestrial exploration, biomedical applications such as surgery and assistive robots, and personal robotics. The course culminates in a hardware project centered on robot integration.

The course addresses advanced mathematical concepts particularly relevant for robotics. The mathematical tools covered in this course are fundamental for understanding, analyzing, and designing robotics algorithms that solve tasks such as robot path planning, robot vision, robot control and robot learning. Topics include complex analysis, optimization techniques, signals and filtering, advanced probability theory, and numerical methods. Concepts will be studied in a mathematically rigorous way but will be motivated with robotics examples throughout the course.

An introduction to the fundamental principles of artificial intelligence from a mathematical perspective. The course will trace the historical development of AI and describe key results in the field. Topics include the philosophy of AI, search methods in problem solving, knowledge representation and reasoning, logic, planning, and learning paradigms. A portion of the course will focus on ethical AI, embodied AI, and on the quest for artificial general intelligence.

This course will introduce students to the topic of machine learning, which is key to the design of intelligent systems and gaining actionable insights from datasets that arise in computational science and engineering. The course will cover the theoretical foundations of this topic as well as computational aspects of algorithms for unsupervised and supervised learning. The topics to be covered include: The learning problem, clustering and k-means, principal component analysis, linear regression and classification, generalized linear models, bias-variance tradeoff, regularization methods, maximum likelihood estimation, kernel methods, the representer theorem, radial basis functions, support vector machines for regression and classification, an introduction to the theory of generalization, feedforward neural networks, stochastic gradient descent, ensemble learning, model selection and validation.

The Robotics Capstone Design course is structured to provide students with an opportunity to integrate and apply the technical knowledge gained throughout their degree program toward the solution of a challenging real-world robotics problem. During the half-year course, students work in small teams and have considerable freedom to explore the design space while developing a complete robotic hardware and software system. The challenge task incorporates all aspects of the "sense-plan-act" robot design paradigm, with designs assessed based on engineering quality and performance relative to a series of benchmarks. In addition, each student completes a critical reflection on their team's performance and the evolution of their experience with design during their undergraduate program. Students are supported by a teaching team comprised of domain experts.

An introduction to aspects of computer vision specifically relevant to robotics applications. Topics include the geometry of image formation, image processing operations, camera models and calibration methods, image feature detection and matching, stereo vision, structure from motion and 3D reconstruction. Discussion of the growing role of machine learning and deep neural networks in robotic vision, for tasks such as segmentation, object detection, and tracking. The course includes case studies of several successful robotic vision systems.

The course addresses fundamentals of mobile robotics and sensor-based perception for applications such as space exploration, search and rescue, mining, self-driving cars, unmanned aerial vehicles, autonomous underwater vehicles, etc. Topics include sensors and their principles, state estimation, computer vision, control architectures, localization, mapping, planning, path tracking, and software frameworks. Laboratories will be conducted using both simulations and hardware kits.

Complementary Studies elective

Part 1 of the 2 Part Entrepreneurship Program

The age of enterprise has arrived. Strategic use of technology in all sorts of businesses makes the difference between success and failure for these firms. Wealth creation is a real option for many and the business atmosphere is ready for you! Increasingly, people are seeing the advantages of doing their own thing, in their own way, in their own time. Entrepreneurs can control their own lives, structure their own progress and be accountable for their own success - they can fail, but they cannot be fired! After all, engineers are the most capable people to be in the forefront of this drive to the business life of the 21st century.

This course is the first of a series of two dealing with entrepreneurship and management of a small company. It is intended the student would take the follow-up course TEP432 as they progress toward their engineering degree. Therefore, it is advisable that the descriptions of both courses be studied, prior enrolling in this one.

This is a limited enrolment course. If the number of students electing to take the course exceeds the class size limit, selection of the final group will be made on the basis of the "Entrepreneur's Test". A certificate will be awarded upon the successful completion of both courses, attesting to the student having passed this Entrepreneurial Course Series at the University of Toronto.

The course is based on real life issues, not theoretical developments or untried options. Topics covered include: Who is an entrepreneur; Canadian business environment; Acquisitions; Different business types (retail, wholesale, manufacturing, and services); Franchising; Human resources, Leadership, Business Law; and many others. Several invited visitors provide the student with the opportunity to meet real entrepreneurs. There will be several assignments and a session project. Please note, the 5 hours per week would be used for whatever is needed at the time. Tutorials will not normally happen as the calendar indicates them.

Humanities and Social Science elective

As students study how language is used to make meaning in diverse contexts, they will hone their own skills in deploying written and oral professional engineering language. The course explores the nature of language across linguistic, discipline and cultural boundaries. Students apply the theoretical knowledge of language and language learning to their own written and oral language performances. In conjunction with this, theories of translation and bilingualism will be introduced to challenge assumptions about the universality of meanings. Weekly lecture and tutorial.

Humanities and Social Science elective

An examination of representations of science/scientists in theatre. Reading and/or viewing of works by contemporary playwrights and related materials on science and culture. Critical essays; in-class discussion and scene study.

Humanities and Social Science elective

Introduces students to the history, theory and practice of communicating science to the public. We first establish a theoretical foundation for understanding the complex relationship between science, scientists, and the public, closely examining techniques and strategies for communicating about science to non-technical readers with a variety of backgrounds and ideological perspectives. We apply these concepts to contemporary case studies in multiple media, focusing on (mis)representations of climate, environmental, and biomedical sciences, breakthroughs in engineering. In doing so, we explore how the shift from traditional news to new media – including videos, podcasts, and social media – has changed how science is communicated to the public, plus the implications of this shift for scientists and engineers.

Humanities and Social Science elective

This course explores Rhetoric historically to understand its development and practically to understand how ideas are constructed, disseminated, shared or imposed. The course explores worldview - the organizing structure by which we view the world - to position the student as rhetorically effective in multiple contexts. Students analyze political, cultural, and scientific discourse from great speeches to advertising to research papers. Students develop their rhetorical, communication, and persuasive abilities.