Engineering Online

Credits: 3.3
Instructor: Mohebbi, Mahdi

Course learning outcomes:

By the end of this course, learners should be able to:

1. Solve parametrized or unparametrized systems of linear equations using Gaussian elimination and back substitution; they will be able to write the augmented matrix of a given system of linear equations, transform it into reduced or row-reduced echelon form using a sequence of elementary row operations, and finally solve the system using back substitution. They will be able to determine the number of solutions as a function of the parameter in case the system of linear equations is parametrized.
2. Perform basic matrix algebraic operations (addition, scaling, multiplication).
3. Understand the notions of eigenvalue, eigenspace, and eigenvector for a given vector space endomorphism; in particular, given a real n √ó n matrix, they will be able to compute the set of all eigenvalues of that matrix, as well as eigenvectors or bases for the eigenspaces corresponding to those eigenvalues.
4. Compute the determinant of a real n √ó n matrix and know its main properties; in particular, they will be able to use the determinant in assessing whether or not a given n √ó n matrix is invertible.
5. Prove linear algebraic results for general vector spaces; these proofs will require mathematical reasoning, will be expressed in precise mathematical language with full mathematical rigor, and will combine various notions seen in different parts of the course, such as vector subspace, linear span, linear independence, linear mapping, and eigenvalue/eigenspace/eigenvector.
6. Understand the mathematical notion of a real vector space, and will be able to determine whether or not a given subset of a real vector space is a vector subspace; in particular, students will be able to work with vector spaces other than the usual Euclidean space Rn.
7. Understand the notions of linear combination and linear span of a family of vectors, and will be able to determine whether or not a given vector is in the linear span of a given family of vectors.
8. Understand the notions of linear dependence and independence of a family of vectors, and will be able to determine whether or not a given family of vectors in a vector space is linearly independent.
9. Understand the notions of basis and dimension of a vector space; they will be able to compute a basis for a given vector space, and use it to compute the dimension of the vector space.
10. Understand the notion of a linear mapping between vector spaces; in particular they will be able to determine whether or not a given mapping between vector spaces is linear.
11. Understand the notions of kernel and image of a linear mapping; in particular, they will be able to compute the kernel and image of a given real matrix, and they will understand the precise relation between the kernel/image of a real matrix and its column vectors.

Credits: 1.7
Instructor: Macdougall, Colin

Course learning outcomes:

By the end of this course, learners should be able to:

1. Draw free-body diagrams.
2. Identify equations of equilibrium.
3. Solve trusses.
4. Calculate internal forces.
5. Create shear force and bending moment diagrams.
6. Solve a frame.
7. Evaluate stresses and strains.
8. Calculate displacements.

Credits: K0.2
Instructor: TBA

Course learning outcomes: TBA

Credits: 3.0
Instructor: Sneep, Jan

Course learning outcomes:

By the end of this course, learners should be able to solve economic analysis problems:

1. Cost concepts and use a variety of cost estimation techniques.
2. Time value of money and solve cash flow analysis problems.
3. Compare a variety of projects using multiple economic approaches.
4. The effect of taxes on project viability and apply to appropriate cash flow analysis.
5. Replacement analysis concepts and apply appropriate cash flow analysis to correctly determine minimum equivalent annual costs.
6. The effect of inflation on project viability and apply to appropriate cash flow analysis.
7. Apply a variety of approaches for dealing with uncertainty and risk associated with projects.
8. Risk management approaches associated with project management.
9. Change management from an organizational behaviour perspective.
10. Recognizing new business opportunities and techniques for generate ideas.
11. Feasibility Analysis.
12. Assessing a new venture’s financial strength and viability.
13. Writing a business plan.
14. Basic management processes and concepts.

Credits: 3.5
Instructor: Koupaie, Ehssan Hosseini

Course learning outcomes:

By the end of this course, learners should be able to:

1. Explain major cellular processes and mechanisms in prokaryotic and eukaryotic cells.
2. Describe the interrelationships between cells and organisms and their environment.
3. Describe the relationship between structure and function on a molecular, cellular and system level.
4. Apply knowledge on biological systems to solve engineering problems of relevance to society.

Exclusion: CHEE 229

Credits: 3.0
Instructor: Duma, Darya

Exclusions: MECH 896, APSC 223

Credits: 4.0
Instructor: Manjikian, Naraig

Course learning outcomes:

By the end of this course, learners should be able to:

1. Understand instruction set architecture to support arithmetic, memory-access, and program branching operations.
2. Understand internal semiconductor memory architecture and the design of basic cache and memory organizations.
3. Use register-transfer notation to specify cycle-by-cycle logic behavior of instruction execution in a basic five-stage processing unit.
4. Write a subroutine-based assembly-language program for specified data processing and input/output operations.

Prerequisites: APSC 142 or APSC 143 or MNTC 313, ELEC 271 or MTHE 217 (MATH 217) or permission of instructor.
Exclusion: CISC 221

Credits: 3.75
Instructor: TBA

Course learning outcomes:

By the end of this course, learners should be able to:

1. Determine electrostatic fields using Coulomb's law and Gauss's law.
2. Determine magnetostatic fields using Biot-Savart's law and Ampere's law.
3. Calculate voltage or current across transverse electromagnetic (TEM) transmission lines.
4. Calculate the induced voltage in time-varying electromagnetic fields using Maxwell's equations.
5. Analyze the transmission line parameters and calculate transient voltage and current of the transmission line.
6. Calculate the gradient, divergence, and curl of various scalar and vector fields.
7. Calculate and describe the motion of systems in simple harmonic motion such as mass-spring systems and simple pendulums.
8. Describe and calculate the motion of transverse and longitudinal waves, and work with basic wave phenomena such as superposition, reflection, standing waves, beats and the Doppler effect.

Prerequisites: APSC 112 or APSC 114, APSC 171, APSC 172, APSC 174

Credits: 1.5
Instructor: Frank, Brian Matthew

Course learning outcomes:

By the end of this course, learners should be able to:

1. Design an electromechanical hardware and software system to control a robotic vehicle to achieve a specified competitive task.
2. Select and control sensors, motors, microcontrollers, and wireless systems in a single mechatronic system.
3. Develop, test, and debug in a high-level language to sense/control a microcontroller output.
4. Using basic electrical/electronic test equipment, perform hardware testing and debugging.
5. Effectively communicate technical ideas in a formal report.
6. Work effectively in a team.

Prerequisites: ELEC 221, ELEC 271
Corequisites: ELEC 252, ELEC 280

Credits: 3.5
Instructor: TBA

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe different types of random variables and identify important distributions.
2. Discuss the law of large numbers and asymptotic behaviours, and the concept of information and entropy.
3. Characterize and identify distribution of functions of multiple random variables and well-known random and point processes.
4. Apply probability theory for modeling uncertainties involved in engineering problems.
5. Solve problems involving probably with conditional probabilities.
6. Calculate different statistics of random variables by manipulating one and two random variables and working with joint distributions.

Prerequisites: APSC 171
Exclusions: MTHE 351 (STAT 351)

Credits: 4.0
Instructor: Pilkey, Keith

Course learning outcomes:

By the end of this course, learners should be able to:

1. Draw a free-body diagram with unknown external and/or internal forces, bending moments and/or torques and apply equations of equilibrium to solve for unknown external and/or internal forces, moments and/or torques.
2. Determine the shear force equations (diagrams) for a beam.
3. Determine the bending moment equations (diagrams) for a beam.
4. Calculate the 2D strain state (normal and/or shear components) from a known amount of deformation.
5. Calculate the 2D stress state (normal and/or shear components) at a given point from a combination of applied normal forces, shear forces, moments and/or torques.
6. Determine the torsional shear stress and angle of twist at a given location in a shaft with circular cross-section subject to applied torques.
7. Calculate the first and/or second moments of area for a complex cross-section.
8. Determine the slope and deflection equations for a beam.

Prerequisites: APSC 111, APSC 171, and APSC 182 or permission of instructor.
Exclusions: CIVL 220, CIVL 230

Credits: 3.5
Instructor: Stacey Zhao

Course learning outcomes:

By the end of this course, learners should be able to:

1. Solve scaling problems using dimensionless groups.
2. Explain control volume (CV) and control mass analysis with reference to Euleria and Lagrangian frames, applied forces and flows.
3. Solve simple flow systems for velocity distributions using continuity and Navier Stokes (NS) equations with appropriate boundary conditions.
4. Calculate pressures and forces on submerged surfaces in a static fluid.
5. Solve flow and force problems in an integral framework using Bernoulli, conservation of mass and momentum.
6. Explain Bernoulli-based energy equations with reference to energy and hydraulic grade lines, static and dynamic pressure.
7. Solve piping system performance problems using Bernoulli with friction, minor losses, pump and turbine performance curves.

Prerequisites: APSC 111

Credits: 3.5
Instructor: Josue Vazquez Becerra

Course learning outcomes:

By the end of this course, learners should be able to:

1. Solving basic initial value problems.
2. Solving linear constant coefficient differential equations.
3. Computing Laplace and inverse Laplace transforms.
4. Using the Laplace transform to solve differential equations.
5. Modeling a mass-spring-damper system or RLC circuit using differential equations.
6. Modeling interconnected fluid reservoirs using differential equations.

Prerequisites: APSC 171, APSC 172, APSC 174

Credits: 3.0
Instructor: Silverberg, Angie

Course learning outcomes:

By the end of this course, learners should be able to:

1. Express and use the tangent/slope and rate of change meanings of the derivative in single variable differential calculus.
2. Construct application models from word problems and use derivatives to investigate properties of the models in single variable differential calculus.
3. Express and use the relationship between integration and the area under a curve/rate graph in single variable integral calculus.
4. Construct application models from word problems and use integrals and/or derivatives to investigate properties of the models in single variable integral calculus.
5. Construct mathematical models from word problems in mathematical modelling.

Prerequisites: MNTC P03 and MNTC P04

Credits: 3.0
Instructor: Tremblay, Eric

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe atomic structure and chemical bonding, and how they relate to the physical properties of ionic, molecular, covalent network, and metallic substances.
2. Perform calculations to an adequate level of precision.
3. Solve problems relating to the physical properties of gases.
4. Apply standard chemistry nomenclature (IUPAC) in the context of describing chemicals (including organic compounds) and chemical reactions.
5. Use stoichiometry to solve common chemistry problems.
6. Use reduction and oxidation chemistry to describe a galvanic cell and other practical applications.
7. Calculate reagent concentrations in solutions.
8. Use the concept of chemical equilibrium to predict the direction of reactions.
9. Solve simplified acid and base problems.

Credits: 3.0
Instructor: Bergeron, Pierre

Course learning outcomes:

By the end of this course, learners should be able to:

1. Produce elevations from differential leveling notes.
2. Calculate coordinates and areas for survey control traverse.
3. Assess measurement for error.
4. Predict the 3-dimensional accuracy of GPS positions.
5. Produce revised ground versus grid distances for construction layout purposes.
6. Operate the main functions of Total Stations and Data Collectors
7. Combine the main functions of Total Stations and Data Collectors in order to produce a pertinent report using previously gathered field data.

Credits: 3.0
Instructor: Cortolezzis, Donna

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe the basic principles of rock failures.
2. Recognize appropriate field and laboratory investigation programs to define rock failure criteria.
3. Analyze data from field and laboratory investigations to define the failure criteria
4. Recognize numerical stress analysis models for excavation design
5. Use various empirical/analytical design methods for excavations such as open stopes, pillars, and open pit slopes
6. Evaluate appropriate support systems for specified ground conditions

Prerequisites: MNTC 302, APSC 182
Exclusions: MINE 325

Credits: 3.0
Instructor: Lambden, Alan

Course learning outcomes:

By the end of this course, learners should be able to:

1. Identify an appropriate mineral deposit type, and use this to identify the geologic factors that control the spatial distribution of grades in the deposit.
2. Compile and validate the data files and data bases required for mineral resource estimation.
3. Statistically analyze and interpret grade distributions, scatterplots and spatial correlation.
4. Explain the advantages and disadvantages of the three most common approaches to grade estimation: geostatistical kriging, inverse-distance interpolation, and the polygonal method.
5. Formulate a set of resource estimation assumptions and parameters, use these to run software to create a resource block model, and then check the reliability of the resulting estimates.

Prerequisites: MNTC 304, MNTC 305 or APSC 151
Exclusions: MINE 467

Credits: 3.0
Instructor: Sari, Asli

Course learning outcomes:

By the end of this course, learners should be able to:

1. Explain how software and hardware interact to link computer programming to actual machine operations.
2. Implement the features of a programming language such as syntax.
3. Transform logical relationships into computer programming elements such as expressions, selection statements, and loops.
4. Use features such as arrays and functions to enhance the efficiency of computer programs.

Prerequisites: MNTC P01
Exclusions: APSC 143

Credits: 4.0
Instructor: Hope, Natalie

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe fluid mechanics fundamentals.
2. Explain ventilation surveys.
3. Analyze ventilation networks (air flow quantity and pressure).
4. Design primary and auxiliary mine ventilation systems in accordance with mine regulations and design criteria.
5. Select appropriate ventilation infrastructure.
6. Perform pipe network analyses.
7. Select appropriate pumps.

Prerequisites: MNTC 302, MNTC 304, and MNTC 305, or APSC 111, APSC 112, APSC 171, APSC 172, and APSC 174.
Exclusions: MINE 339

Credits: 3.5
Instructor: Macauley, Doug

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe the nature and components of global minerals supply, demand, trade and price.
2. Identify national and international policies, regulations and treaties relevant to the minerals industry.
3. Solve structured problems using economic analysis concepts (e.g. time value of money, discounting) and financial analysis tools (e.g. Net Present Value (NPV), Internal Rate of Return (IRR), payback period).
4. Describe the estimation of mineral resources and mineral reserves, the feasibility assessment process and different types of reports, and the disclosure of the results of work in these areas under National Instrument 43-101.
5. Apply economic and financial tools to valuation of companies, evaluation of projects, and strategic planning.
6. Discover how risk and uncertainty are addressed in the techniques and processes of mineral economics.
7. Discover sources and types of equity and debt financing for mining companies and projects.
8. Examine the impact of sustainability initiatives and frameworks on mining companies and projects, and ways in which sustainability is increasingly being reflected in activities studied in this course.

Prerequisites: APSC 221 and MNTC 305, or permission of the Mining Department
Exclusions: MINE 330

Credits: 3.0
Instructor: Ortiz, Julian

Course learning outcomes:

By the end of this course, learners should be able to:

1. Describe surface mining techniques
2. Explain how the environment is impacted by surface mining
3. Describe the difference between estimating and simulating an orebody block model. Calculate ore cut off grades given various constraints. Calculate bulk density.
4. Apply pit limit analysis algorithms in two dimensions.
5. Sequence blocks using constraints such as various slope stability angles, mining capacity and milling capacity.
6. Design production rates for a surface mining operation. Relate production rates to mining and milling capacities.
7. Describe mine planning fundamentals and formulate short-term mine plans. Relate capacity selection to market structure and economic considerations. Calculate whether blocks are ore or waste using the minimum loss or maximum profit formulas. Delineate dig limits and describe the relationship between dig limits and equipment size. Design a bed-blending operation. Reconcile actual to planned grades. Develop a gap management strategy.
8. Select equipment for excavation, loading, hauling using the time value of money and compatibility to a proposed mine design.
9. Describe the current state of automation for each type of equipment in open pit mining. Be able to assess the future trends of automated equipment. Describe support services needed and the impact automation will have on the workforce.
10. Describe bench geometry and design benches in open pit mines. Solve slope stability problems including calculation of a safety factor.
11. Identify sources of water in surface mines. Describe current dewatering strategies and design a dewatering circuit. Select the correct type and size of pumps based for a dewatering circuit.
12. Critique haul road designs using best practices in safety and operational design. Describe the importance of haul roads, design and maintain haul roads.
13. List the elements of open pit operating costs. Describe open pit capital costs. Evaluate the impact changing operating and capital costs have on equipment selection
14. Analyze case studies using learning objectives 1 through 13.

Prerequisites: MNTC 305, MNTC 307, MNTC 311, and MNTC 314 or permission of the department.
Exclusions: MINE 341

Credits: 3.0
Instructor: Daneshmend, Laeeque

Course learning outcomes:

By the end of this course, learners should be able to:

1. Explain qualitative and quantitative reliability and maintenance concepts including risk.
2. Justify the selection of maintenance policies and their appropriate applications in mining.
3. Explain the relationship between maintenance organizational structures and processes with respect to mining operations taking into account practical realities in the mining context.
4. Design maintenance organizational structures including work-flow processes.
5. Apply relevant analytical techniques for the prioritization of maintenance activities and resources; including Pareto analysis, Failure Mode Analysis, and Failure Rate curves.
6. Select appropriate maintenance policies through a structured methodology (RCM), based on application of analytical techniques and incorporating costs.

Prerequisites: MNTC 302 and MNTC 304 or APSC 171, APSC 172, and APSC 182