Numerical Methods In Chemical Engineering

Mode of Delivery

Face to Face

Prerequisites and Co-Requisites

None

Recommended Optional Programme Components

YOK

Course Contents

Introduction to numerical methods, error types, roots of equations, solving systems of linear equations, systems of nonlinear equations, interpolation, numerical integration and differentiation, solving systems of systems of ordinary differential equations, Statistical analysis (regression and correlation), using MATLAB for problem solving.

Weekly Schedule

1) Introduction to numerical methods, error definitions, Taylor theorem
2) Roots of equations with one-variable, Bisection and Secant methods
3) Roots of equations with one-variable, Newton Raphson and Regula Falsi methods
4) Matrix operations, Solution of linear equation systems - Inverse matrix method
5) Solution of linear equation systems - Cramer and Gauss elimination methods
6) Solution of nonlinear equation systems
7) Matlab case studies
8) Midterm examination/Assessment
9) Matlab case studies
10) Interpolation with finite divided differences, Lagrange interpolation method
11) Curve fitting - Linear interpolation, quadratic interpolation, least squares method, multiple regression
12) Matlab case studies
13) Numerical integration - Trapezoidal and Simpson methods
14) Numerical differentiation, Solution of ordinary differential equations - Euler and Runge-Kutta methods
15) MATLAB practice
16) Final examination

Recommended or Required Reading

1- Ders Notları
2- http://bulentoruc.net/

Planned Learning Activities and Teaching Methods

1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Self Study
6) Problem Solving

Assessment Methods and Criteria

Contribution of Semester Studies to Course Grade	30%
Number Percentage Semester Studies Midterm Examination 1 70% Quiz 1 30%
Contribution of Final Examination to Course Grade	70%
Total	100%

Language of Instruction

English

Work Placement(s)

Not Required