Numerical Methods in Mechanical Engineering
Learning Objective:To introduce the student to basic numerical analysis techniques which are used to solve science and engineering problems. To provide students with experience programming some of these techniques to help them gain familiarity with the methods and the errors associated with them.
Description:This course will cover a range of numerical analysis techniques related to solving systems of linear algebraic equations, matrix eigenvalue problems, nonlinear equations, polynomial approximation and interpolation, numerical integration and differentiation, ordinary and partial differential equations.
Topics Covered:Introduction; Computer Programming Languages and Software; Systems of Linear Algebraic Equations; Matrix Eigenvalue Problems; Nonlinear Equations; Polynomial Approximation and Interpolation; Numerical Differentiation and Integration; Ordinary Differential Equations; Partial Differential Equations
Prerequisites:Graduate level standing in a science or engineering discipline. Some background in MATLAB, FORTRAN, PYTHON, or C and computer programming
Applied / Theory:65 / 35
Web Content:includes lecture notes, syllabus, homework solutions, grades, references, sample exam, links. Mixable will also support course.
Homework:Bi-weekly assignments involving both hand written and computer programming
Exams:One in-class midterm and one two-hour final exam
Textbooks:Required--"A Friendly Introduction to Numerical Analysis", Brian Bradie, Prentice Hall 2006, ISBN 9780130130549
Computer Requirements:It is highly recommended that you develop, and run all your codes using the Unix or Linux environment. This will be available when you create an account and we give you access to workspace in nanohub.org.
Tutorial on Unix/Linux:
Pick an editor:
Numerical Recipes in Fortran, Numerical Recipes in C-http://nanohub.org
Students should contact the ITaP Help Desk (http://www.itap.purdue.edu/help/) for Blackboard questions