# SKKK 2133 Chemical Engineering Computation

SYNOPSIS

This course introduces students to some numerical techniques in solving problems that could not be solved analytically. Students will be exposed to the numerical solution for simultaneous algebraic equation and non linear equations. Besides that, student will learn about interpolation, numerical differentiation and numerical solution for initial value problem of linear ordinary differential equations. Since numerical methods are an approximation method, the accuracy of numerical solution will be calculated.

By the end of the course, students should be able to:

1. Recognize the difference between analytical and numerical solutions
2. Use bracketing and open methods to solve root of equation problems
3. Solve simultaneously sets of linear algebraic equations using Naïve Gauss Elimination, Gauss-Jordan Elimination, LU Decomposition and Gauss-Siedel methods
4. Differentiate the fundamental difference between regression and interpolation and able to solve the numerical method problems
5. Solve numerical differentiation problems using suitable numerical differentiation formulas
6. Use formula and error equations for Trapezoidal and Simpson’s rules to evaluate the numerical method integral
7. Solve Ordinary Differential Equation problems using Euler’s,Heun’s and Runge Kutta methods
8. Ethics and Lifelong Learning

SLIDE

CHAPTER 1- INTRODUCTION TO NUMERICAL METHOD

CHAPTER 2- APPROXIMATION OF ERROR

CHAPTER 3- ROOTS OF EQUATION

CHAPTER 4 – LINEAR ALGEBRAIC EQUATION

CHAPTER 5 – CURVE FITTING

MATHLAB PART 1

MATHLAB PART 2

m script – bisection

m script – euler

m script – linear regression

m script – Naive Gauss

m script – Newton Raphson

m script – Trapezoidal

TEST QUESTION SAMPLES

TEST I-APRIL 2015

TEST 2 – May 2015