Mechatronics Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Mechatronics Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Mechatronics Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05550002 | Numerical Analysis | 3 | Autumn | 5 | 3+0+0 | 5 | 5 |
| Course Type | Compulsory |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Adem YILMAZ |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Adem YILMAZ | - | [email protected] |
Course Content
Mathematical priorities, Equations with one variable, Polynomial Interpolation, Numerical Integration and Differantiation, Ordinary Differantial Equations
Objectives of the Course
This course aims to teach fundamentals of numerical methods, enhance students'programming skills using the MATLAB environment to implement algorithms, to teach the use of MATLAB as a tool (using built-in functions) for solving problems in science and engineering.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P2 | Ability to identify, formulate and solve complex Mechatronics Engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 5 |
| P4 | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Mechatronics Engineering applications; Ability to use information technologies effectively | 4 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Ability to solve nonlinear equations | P.2.48 | 1 |
| O2 | Ability to apply curve fitting methods | P.2.49 | 1 |
| O3 | Ability to apply numerical integration methods | P.2.50 | 1 |
| O4 | Ability to apply numerical differentiation methods | P.2.51 | 1 |
| O5 | Ability to apply numerical analysis methods with a programming language | P.4.26 | 7 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to numerical analysis |
| 2 | MATLAB Fundamentals |
| 3 | Programming with MATLAB |
| 4 | Approximations and round-off errors, truncation errors, Taylor series, |
| 5 | Roots: Bracketing methods |
| 6 | Roots: Open methods |
| 7 | Polynomial Interpolation |
| 8 | Polynomial Interpolation |
| 9 | Numerical Integration |
| 10 | Numerical Differantiation |
| 11 | Linear regression |
| 12 | Linear regression |
| 13 | Numerical Ordinary differantial equations |
| 14 | Numerical Ordinary differantial equations |
Textbook or Material
| Resources | Steven C. Chapra, Applied Numerical Methods with MATLAB, 3rd Edition, McGraw Hill, 2012 |
| Steven C. Chapra, Applied Numerical Methods with MATLAB, 3rd Edition, McGraw Hill, 2012 |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | 1 | 30 (%) |
| Midterms | 1 | 30 (%) |
| Final Exam | 1 | 40 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 20 | 20 |
| Quiz | 1 | 15 | 15 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 25 | 25 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 144 | ||
| Total Work Load / 30 | 4,80 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 | P4 |
|---|---|---|---|
| O1 | Ability to solve nonlinear equations | 5 | - |
| O2 | Ability to apply curve fitting methods | 5 | - |
| O3 | Ability to apply numerical integration methods | 5 | - |
| O4 | Ability to apply numerical differentiation methods | 5 | - |
| O5 | Ability to apply numerical analysis methods with a programming language | - | 4 |