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 | Area Elective | 3 | 1 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| (MATH275 veya MATH231) |
| Course Language | English |
|---|---|
| Course Type | Technical Elective 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 | Adequate knowledge in mathematics, science and subjects specific to the software 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. | |||||
| 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 software engineering applications; the ability to utilize information technologies effectively. | |||||
| 5 | The ability to gather data, analyze and interpret results for the investigation of complex engineering problems or research topics specific to the software engineering discipline. | |||||
| 6 | The ability to work effectively in inter/inner disciplinary teams; ability to work individually. | |||||
| 7 | Effective oral and written communication skills in Turkish; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions. | |||||
| 8 | 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 receive clear and understandable instructions. | |||||
| 9 | Recognition of the need for lifelong learning; the ability to access information and follow recent developments in science and technology with continuous self-development | |||||
| 10 | The ability to behave according to ethical principles, awareness of professional and ethical responsibility. | |||||
| 11 | Knowledge of the standards utilized in software engineering applications. | |||||
| 12 | Knowledge on business practices such as project management, risk management and change management. | |||||
| 13 | Awareness about entrepreneurship, and innovation. | |||||
| 14 | Knowledge on sustainable development. | |||||
| 15 | Knowledge of the effects of software engineering applications on the universal and social dimensions of health, environment, and safety. | |||||
| 16 | Awareness of the legal consequences of engineering solutions. | |||||
| 17 | An ability to apply algorithmic principles, mathematical foundations, and computer science theory in the modeling and design of computer-based systems with the trade-offs involved in design choices. | |||||
| 18 | The ability to apply engineering approach to the development of software systems by analyzing, designing, implementing, verifying, validating and maintaining software systems. | |||||
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 | ||