Numerical Methods (ENE307) Ders Detayları

Course Name Corse Code Dönemi Lecture Hours Uygulama Saati Lab Hours Credit ECTS
Numerical Methods ENE307 5. Semester 2 2 0 3 4
Pre-requisite Course(s)
MATH 275
Course Language İngilizce
Course Type Compulsory Departmental Courses
Course Level Lisans
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Demonstration, Discussion, Question and Answer, Drill and Practice.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course is designed to teach fundamental numerical methods to provide approximate solutions for various engineering problems.
Course Learning Outcomes The students who succeeded in this course;
  • Understand both direct and iterative methods in the solution of engineering problems.
  • Implementation of numerical methods using MATLAB.
  • Understanding numerical errors. Provide numerically stable and convergent numerical algorithms.
  • Analyze and use numerical algorithms for integration.
  • Construct polynomial approximations to functions by interpolation. Use of linear regression for curve fitting.
  • Use numerical methods to solve nonlinear equations.
Course Content Modeling, Euler’s method, Truncation and rounding errors. Taylor series. Roots of equations: Bracketing and Open methods. Matrices. Solutions of linear algebraic equations; Gauss elimination and decomposition methods. Curve fitting; Least-squares regression, Interpolation. Numerical differentiation and integration.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to Numerical Methods. Chapter 1
2 MATLAB Fundamentals and Programming with MATLAB Chapters 2&3
3 Round-off and Truncation Errors Chapter 4
4 Roots: Bracketing Methods Chapter 5
5 Roots: Open Methods Chapter 6
6 Optimization Chapter 7
7 Linear Algebraic Equations: Naive Gauss and Gauss Jordan Chapter 8-11
8 Linear Algebraic Equations: Gauss-Seidel and Modified Gauss- Seidel Chapter 12
9 Midterm Exam
10 Least Squares Regression Chapter 13
11 Least Squares Regression Chapter 14
12 Interpolation: Newton and Lagrange, Spline Chapter 15&16
13 Numerical integration: Trapezoidal and Simpson’s rules, Gaussian rules Chapter 17&18
14 Numerical Differentiation Chapter 19
15 Ordinary Differential Equations Chapter 20&21&22
16 Final Exam

Sources

Course Book 1. Applied Numerical Methods with MATLAB for Engineers and Scientists, 2nd Edition, Steven C. Chapra, Tufts University, McGraw-Hill, 2008
Other Sources 2. Numerical Methods for Engineers, S.C. Chapra & R.P. Canale, 5th Edition, McGraw-Hill, 2006
3. J.H.Mathews & K.D. Fink, Numerical Methods Using Matlab, 4th Edition, Pearson, 2004
4. G.Lindfield, J. Penny, “Numerical Methods Using MATLAB”, Second Edition Prentice Hall, 2000
5. L. V. Fausett, “Applied Numerical Analysis Using MATLAB 2/E”, 2008, Prentice Hall.
6. MATLAB® Student Version Release 12, including MATLAB 6 and Simulink® 4, The Math Works Inc. 2001

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation 1 10
Laboratory 1 30
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 10 20
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 40
Final Exam/Final Jury 1 40
Toplam 14 140
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science, and engineering. X
2 An ability to design and conduct experiments, as well as to analyze and interpret data. X
3 An ability to design a system, component, or process to meet desired needs. X
4 An ability to function on multi-disciplinary teams. X
5 An ability to identify, formulate, and solve engineering problems. X
6 An understanding of professional and ethical responsibility. X
7 An ability to communicate effectively. X
8 The broad education necessary to understand the impact of engineering solutions in a global and societal context. X
9 Recognition of the need for, and an ability to engage in life-long learning. X
10 Knowledge of contemporary issues. X
11 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. X
12 Skills in project management and recognition of international standards and methodologies

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 101