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 Lecturer(s) |
|
| 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;
|
| 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 | Has the ability to apply scientific knowledge gained in the undergraduate education and to expand and extend knowledge in the same or in a different area | |||||
| 2 | Can apply gained knowledge and problem solving abilities in inter-disciplinary research | |||||
| 3 | Has the ability to work independently within research area, to state the problem, to develop solution techniques, to solve the problem, to evaluate the obtained results and to apply them when necessary | |||||
| 4 | Takes responsibility individually and as a team member to improve systematic approaches to produce solutions in unexpected complicated situations related to the area of study | |||||
| 5 | Can develop strategies, implement plans and principles on the area of study and can evaluate obtained results within the framework | |||||
| 6 | Can develop and extend the knowledge in the area and to use them with scientific, social and ethical responsibility | |||||
| 7 | Has the ability to follow recent developments within the area of research, to support research with scientific arguments and data, to communicate the information on the area of expertise in a systematically by means of written report and oral/visual presentation | |||||
| 8 | To have an oral and written communication ability in at least one of the common foreign languages ("European Language Portfolio Global Scale", Level B2) | |||||
| 9 | Has software and hardware knowledge in the area of expertise, and has proficient information and communication technology knowledge | |||||
| 10 | Follows scientific, cultural, and ethical criteria in collecting, interpreting and announcing data in the research area and has the ability to teach. | |||||
| 11 | Has professional ethical consciousness and responsibility which takes into account the universal and social dimensions in the process of data collection, interpretation, implementation and declaration of results in mathematics and its applications. | |||||
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 | ||