ECTS - Numerical Methods for Engineers

Numerical Methods for Engineers (MATH380) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Numerical Methods for Engineers MATH380 3 1 0 3 5
Pre-requisite Course(s)
MATH275 Linear Algebra
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Experiment, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This undergraduate course is designed for engineering students. The objective of this course is to introduce some numerical methods that can be used to solve mathematical problems arising in engineering that can not be solved analytically. The philosophy of this course is to teach engineering students how methods work so that they can construct their own computer programs.
Course Learning Outcomes The students who succeeded in this course;
  • solve a non-linear equation in science and engineering by using the MATLAB programming.
  • solve a linear system by using a suitable method in science and engineering via the MATLAB programming.
  • find the eigenvalues and eigenvectors of a given matrix.
  • learn how to use the interpolation.
  • learn how to derive the approximations for the derivatives.
  • learn the approximate computation of an integral using numerical techniques.
Course Content Solution of nonlinear equations, solution of linear systems, eigenvalues and eigenvectors, interpolation and polynomial approximation, least square approximation, numerical differentiation, numerical integration.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 1. Preliminaries: Approximation, Truncation, Round-off errors in computations. pp. 2 - 41
2 2. Solution of Nonlinear Equations 2.1. Fixed Point 2.2. Bracketing Methods for Locating a Root pp. 41 - 51
3 2.3. Initial Approximation and Convergence Criteria 2.4. Newton-Raphson and Secant Methods pp. 62 - 70
4 2.6. Iteration for Non-Linear Systems (Fixed Point for Systems) 2.7. Newton Methods for Systems pp. 167 - 180
5 3. Solution of Linear Systems 3.3. Upper-Triangular Linear Systems (Lower-Triangular) 3.4. Gaussian Eliminatian and Pivoting pp. 120 - 137
6 3.5. Triangular Factorization (LU) pp. 141 - 153
7 Midterm
8 3.7. Doğrusal sistemler için iteratif metotlar (Jacobi / Gauss Seidel Metotları) pp. 156 - 165
9 11. Eigenvalues and Eigenvectors 11.2. Power Method (Inverse Power Method) pp. 588 – 592 pp. 598 - 608
10 4. Interpolation and Polynomial Approximation 4.2. Introduction to Interpolation 4.3. Lagrange Approximation and Newton Approximation pp. 199 - 228
11 5. Curve Fitting 5.1. Least-squares Line pp. 252 - 259
12 5.3. Spline fonksiyonları ile interpolasyon pp. 279 - 293
13 6. Numerical Differentiation 6.1. Approximating the Derivative 6.2. Numerical Differentiation Formulas pp. 320 - 348
14 7. Numerical Integration 7.1. Introduction to Quadrature 7.2. Composite Trapezoidal and Simpson’s Rule pp. 352 - 374
15 Review
16 Genel Sınav

Sources

Course Book 1. J. H. Mathews, K. D. Fink, Numerical Methods Using Matlab, 4th Edition, Prentice Hall, 2004.
Other Sources 2. S. C. Chapra, Applied Numerical Methods with MATLAB for Engineers and Scientists, 3rd Edition, Mc Graw Hill Education, 2012.
3. A. Gilat, V. Subramaniam, Numerical Methods for Engineers and Scientists: An introduction with Applications Using MATLAB, 3rd Edition, John Wiley & Sons, Inc. 2011.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory 2 10
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 50
Final Exam/Final Jury 1 40
Toplam 5 100
Percentage of Semester Work 0
Percentage of Final Work 100
Total 100

Course Category

Core Courses
Major Area Courses
Supportive Courses X
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 Adequate knowledge in mathematics, science and subjects specific to the computer engineering discipline; the ability to apply theoretical and practical knowledge of these areas to complex engineering problems. X
2 The ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose. X
3 The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose.
4 The ability to develop, select and utilize modern techniques and tools essential for the analysis and determination of complex problems in computer engineering applications; the ability to utilize information technologies effectively.
5 The ability to design experiments, conduct experiments, gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the computer engineering discipline.
6 The ability to work effectively in inter/inner disciplinary teams; ability to work individually
7 Effective oral and writen communication skills in Turkish; the knowledge of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and to receive clear and understandable instructions.
8 Recognition of the need for lifelong learning; the ability to access information, to follow recent developments in science and technology.
9 The ability to behave according to ethical principles, awareness of professional and ethical responsibility; knowledge of the standards utilized in computer engineering applications.
10 Knowledge on business practices such as project management, risk management and change management; awareness about entrepreneurship, innovation; knowledge on sustainable development.
11 Knowledge on the effects of computer engineering applications on the universal and social dimensions of health, environment and safety; awareness of the legal consequences of engineering solutions.
12 An ability to describe, analyze and design digital computing and representation systems. X
13 An ability to use appropriate computer engineering concepts and programming languages in solving computing problems.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory 16 1 16
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 2 10 20
Prepration of Final Exams/Final Jury 1 13 13
Total Workload 77