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CE 329 Structural Analysis (Undergraduate)
This course is aimed at introducing classical methods of structural analysis. It concentrates on the analysis of statically determinate and indeterminate structures. Various methods will be presented to compute displacements, with the use of virtual work emphasized. For analysis of statically indeterminate structures, the force method of analysis (also called flexibility method) will be emphasized. Displacement-based methods will also be introduced including slope deflection method and moment distribution. Structures examined in this course will be modeled as planar trusses, beams and/or frame structures.
CE 311S Probability and Statistics for Civil Engineers (Undergraduate)
This course is required for all undergraduate civil and architectural engineering students. The course introduces students to fundamental concepts of probability and statistics that will help them evaluate and manage uncertainty and risk in civil engineering design problems.
CE 382H Structural Health Monitoring and Nondestructive Evaluation (Graduate)
The course covers the principal methods used for non-destructive evaluation (NDE) and structural health monitoring (SHM) of structural components. Relevant physical principles of continuum mechanics, electrical engineering, acoustics and elastic wave propagation underlying the experimental methods will be covered. Sensor data acquisition and interrogation and ultrasonic digital signal processing will be addressed. Laboratory demonstrations will be given on selected topics. The topic is extremely relevant to the engineering profession as there is an ever increasing demand to ensure the safety and assess the state of health of existing structures. It also provides the basis for breadth in the application of the students’ knowledge to civil engineering.
CE 397 Probability Analysis and Design (Graduate)
The course is intended for graduate students who have not been exposed to probabilistic concepts in their undergraduate studies. It is an introductory but mathematically rigorous course in probability and statistical analysis with engineering applications. By the end of the course, students should be able to: (1) use basic probability concepts (set theory, statistical independence, conditional probability); (2) set up and work with both discrete and continuous random variables; (3) know what expectation and variance mean and be able to compute them; (4) compute the covariance and correlation between jointly distributed variables; (5) create and interpret frequency diagrams and histograms; (6) find the maximum likelihood estimate for a model parameter.
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