Building Engineering

Infrastructure Protection
A fully integrated protection scheme is necessary to efficiently implement an Infrastructure Resilience Plan to assure operational survival following a catastrophic event. Building on the first principles of security integration and fortifications practice, illustrated with case studies through history, the students explore site security surveys, different tools, mitigation methods and models in common use and the assumptions and technology behind them in order to make informed decisions on how to approach and solve an infrastructure protection problem for the full range of event types. This is then practised in partnership with industry, analysing real security integration issues for real clients, to whom the students will present their protection schemes. More info

Geotechnical Engineering II
Building on CME321, more complex aspects of geotechnical analysis and design are considered. Topics include: mineralogy; soil identification and classification; laboratory- and field-based soil index tests; correlations of index test results to engineering properties; vertical stress distribution; soil-foundation interaction; volume change and consolidation of clay and settlement. Shear strength of soil and slope stability analysis are also discussed. Laboratories are held for soil identification and classification, and confined triaxial compression tests of clay and sand.

View full course description in the Engineering Undergrad Academic Calendar.

Reinforced Concrete II
This course covers the behaviour and ultimate strength of reinforced concrete structures. Members subjected to flexure, axial load, shear and torsion are treated. Detailing of reinforcement, the design of floor systems and the design of shear walls are covered. An introduction to the seismic design of reinforced concrete structures is made. Emphasis is given to the relationship between recent research results and current building codes. A brief treatment of the behaviour and design of masonry walls is included.

View full course description in the Engineering Undergrad Academic Calendar.

Reinforced and Prestressed Concrete Structures
Methods for predicting the load-deformation response of reinforced and prestressed concrete elements and structures are reviewed. The use of computer based analytical procedures are illustrated in terms of case studies. The evaluation and repair of concrete buildings, bridges and other civil engineering structures are explained.


Prerequisite: CIV 517H

Scheduling
This course takes a practical approach to scheduling problems and solution techniques, motivating the different mathematical definitions of scheduling with real world scheduling systems and problems. Topics covered include: job shop scheduling, timetabling, project scheduling, and the variety of solution approaches including constraint programming, local search, heuristics, and dispatch rules. Also covered will be information engineering aspects of building scheduling systems for real world problems.


Prerequisite: MIE262H1.

Statistical Models in Empirical Research
This course covers various statistical models used in empirical research, in particular human factors research, including linear regression, mixed linear models, non-parametric models, generalized linear models, time series modeling, and cluster analysis. For various observational and experimental data, students will be proficient in generating relevant hypotheses to answer research questions, selecting and building appropriate statistical models, and effectively communicating these results through interpretation and presentation of results. Basic knowledge in probability, statistics, and experimental design is required. The course will not focus on the design of experiments. In addition to homework assignments and exams, the students will review and critique journal articles and conference papers for the validity of the use of various statistical models. The students will work on a term long project of their choice and will be encouraged to relate this assignment to their current research projects. The examples used in class and the assignments will be drawn from human factors research. However, the students will not be required to use human factors data for their project. More Info