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 | 4. Semester | 3 | 1 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| (MATH275 veya MATH231) |
| Course Language | English |
|---|---|
| Course Type | Compulsory Departmental Courses |
| 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 | 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 | Engineering Knowledge: Knowledge of mathematics, science, fundamental engineering, computational sciences, and related engineering disciplines; the ability to apply this knowledge to solve complex engineering problems. | X | ||||
| 2 | Problem Analysis: The ability to identify, formulate, and analyze complex engineering problems using fundamental scientific, mathematical, and engineering knowledge, considering the relevant UN Sustainable Development Goals. | |||||
| 3 | Engineering Design: The ability to design creative solutions to complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, considering realistic constraints and conditions. | |||||
| 4 | Techniques and Tool Usage: The ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while being aware of their limitations. | |||||
| 5 | Research and Investigation: The ability to use research methods, including literature review, designing experiments, conducting experiments, collecting data, analyzing and interpreting results, to investigate complex engineering problems. | |||||
| 6 | Global Impact of Engineering Applications: Information about the impacts of engineering applications on society, health and safety, the economy, sustainability and the environment within the framework of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions. | |||||
| 7 | Engineering Ethics: Knowledge of ethical responsibility and adherence to engineering professional principles; awareness of impartiality, lack of discrimination, and inclusivity. | |||||
| 8 | Individual and Teamwork: The ability to work effectively individually and as a team member or leader in interdisciplinary and multidisciplinary teams (face-to-face, on-line, or hybrid). | |||||
| 9 | Oral and Written Communication: The ability to communicate effectively orally and in writing on technical topics, considering the diverse differences of the target audience (education, language, profession, etc.). | |||||
| 10 | Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation. | |||||
| 11 | Lifelong Learning: The ability to learn independently and continuously, adapt to new and emerging technologies, and think critically about technological change. | |||||
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 | ||