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COURSE SYLLABUS – EE 332
COURSE TITLE ENGLISH CODE/NO CODE/NO ARABIC CREDITS
Th. Pr. Tr. Tu. Total Numerical Methods in
Engineering EE 332 333 ك ـه 2
2 -- -- 3
Pre-requisites: EE 201, MATH 204
Course Role in Curriculum Required or Elective:
Required
A pre-requisite for:
ChE 321
Catalogue Description:
Introduction. Solution of non-linear equations. Solution of large systems of linear equations.
Interpolation. Function approximation. Numerical differentiation and integration. Solution of the initial value problem of ordinary differential equations.
Textbooks:
S.C. Chapra and R.P. Canale, Numerical Methods for Engineers, 6th Ed., McGraw – Hill, 2009 Supplemental Materials:
J.R. Rice, Numerical Methods, Software, and Analysis, 2nd ed, McGraw-Hill, 1992
Course Learning Outcomes:
By the completion of the course the student should be able to:
1. Solve equations in one variable.
2. Solve set of linear and nonlinear equations in multi variables.
3. Use interpolating polynomial to interpolate experimental data.
4. Use curve fitting to interpolate experimental data.
5. Compute differentiation and integration numerically.
6. Solve the initial value problem.
7. Use structured programming to implement the numerical methods.
8. Analyze the error performance of the different numerical methods.
Topics to be Covered: Duration in Weeks
1. Mathematical backgrounds and Computer Programming
Revision 1 2. Analytical vs. Numerical methods. True and Approximation
Errors 1
3. Solution of equations in one variable: Bisection method, Fixed Point Iterative method, Newton-Raphson Method, Secant Method, Graphical Method. Conditions of convergence of root finding algorithms
2
4. Solution of linear system of equations with several variables:
Gaussian eliminations and backward substitution, Gauss- Jordan, Determinant of a Matrix, Matrix Inversion using LU- decomposition, Iterative techniques for solving linear systems:
Jacobi’s method and Gauss-Seidel method. Conditions of convergence of Iterative methods
3.5
5. Solution of non-linear system Of equations with several variables: Fixed Point method and Newton's method. Condition of convergence.
1
2
6. Interpolation using Newton’s Divide-Difference interpolating
polynomial and Lagrange interpolating polynomial 1 7. Curve fitting using Discrete Least-Square Approximation
method. Determining the goodness of the fitted curve 1.5 8. Numerical Differentiation: Numerical methods for 1st and 2nd
derivatives of a function based on Taylor series. Analysis of accuracy of numerical differentiation methods
1 9. Numerical Integration: Single and Composite Trapezoidal and
Simpson’s rules. Analysis of accuracy of numerical integration methods
1 10. Solution of Initial Value Problems using Euler Method.
Analysis of accuracy of Euler’s method 1
Key Student Outcomes addressed by the course: (Put a sign) (a) an ability to apply knowledge of mathematics, science, and engineering
(b) an ability to design and conduct experiments, as well as to analyze and interpret data
(c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
(d) an ability to function on multidisciplinary teams
(e) an ability to identify, formulate, and solve engineering problems (f) an understanding of professional and ethical responsibility (g) an ability to communicate effectively
(h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context
(i) a recognition of the need for, and an ability to engage in life-long learning (j) a knowledge of contemporary issues
(k) an ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice. √
Key Student Outcomes assessed in the course: (k)
