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Catalog Description

• This course introduces the concepts of analytic modeling and computer simulation, using small projects drawn from the multidisciplinary areas of Computational Engineering Science. Those areas covered span biology, chemistry, applied mathematics, and physics, as well as all areas of engineering. Models will progress sequentially through problem statement, mathematical model, approximations and analytic solution, discrete model, object-oriented model, implementation and simulation, visualization, and comparison to analysis, experiment and observation. Part I (this course) stresses modeling, while Part II (E170B) stresses simulation and visualization.

Course Prerequisite(s)

• Junior/Senior/Graduate standing, Engin. 77N, Math 53, Math

Textbook(s) and/or other required material

• G. Lindfield and J. Penny, Numerical Methods Using MatLab, Prentice-Hall (2000).
• Also on available at the Engineering library: W. Press et al., Numerical Recipes in C, D. Hanselman, Mastering MatLab 6

Course objective

• Gain skills in modeling and simulation of real world problems. Emphasis in Part I is on creating models from a general problem, making the models tractable for analytic and computational treatment.

Assessment of student progress toward course objectives

• Assignments include weekly readings, weekly to biweekly homework assignments, and a take-home final exam project.
• Grades are based on homework (70%) and the final project (30%).