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Johns Hopkins University | EN.560.618

Probabilistic Methods in Civil Engineering and Mechanics

3.0

credits

Average Course Rating

(3.93)

Covers probabilistic computational modeling in civil engineering and mechanics: Monte Carlo simulation, sampling methods and variance reduction techniques, simulation of stochastic processes and fields, and expansion methods. Applications to stochastic finite element, uncertainty quantification, reliability analysis, and model verification and validation.

Fall 2014

Professor: Michael Shields

(3.93)

Students praised this class for provided a ‘crash course’ in probability theory and advanced probability topics. Perceived issues with the course varied and included a belief that students weren’t provided enough example calculations which made it hard for students to master topics that were explained during lectures. Suggestions for improvement largely consisted of requests for students to be given additional example problems and short homework assignments so that they could better master the material. Prospective students should know that students found that the course was chal enging and math intensive. Student also found that having a background in probability theory was helpful for success in the course.

Lecture Sections

(01)

No location info
D. Giovanis
15:00 - 16:15
16 open / 24 seats