ECTS - Numerical Solution of Differential Equations
Numerical Solution of Differential Equations (MDES620) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Numerical Solution of Differential Equations | MDES620 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Natural & Applied Sciences Master's Degree |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
Course Lecturer(s) |
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Course Objectives | This course is designed to give engineering students in graduate level the expertise necessary to understand and use computational methods for the approximate/numerical solution of differential equations problems that arise in many different fields of science. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Numerical solution of initial value problems; Euler, multistep and Runge-Kutta methods; numerical solution of boundary value problems; shooting and finite difference methods; stability, convergence and accuracy; numerical solution of partial differential equations; finite difference methods for parabolic, hyperbolic and elliptic equations; explic |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | 1. Week Review to differential equations 2. Week Numerical solutions of initial value problems; Euler, multistep and Runge-Kutta methods 3. Week Numerical solutions of initial value problems; Euler, multistep and Runge-Kutta methods 4. Week Numerical solutions of boundary value problems; finite difference methods 5. Week Numerical solutions of boundary value problems; finite difference methods 6. Week Stability, convergence and accuracy of the numerical techniques given 7. Week Stability, convergence and accuracy of the numerical techniques given 8. Week Midterm Exam 9. Week Partial differential equations and their solutions 10. Week Numerical solution of partial differential equations; finite difference methods 11. Week Numerical solution of partial differential equations; finite difference methods 12. Week Numerical solution of parabolic, hyperbolic and elliptic equations by finite difference methods 13. Week Explicit and implicit methods, Crank-Nicolson method 14. Week Explicit and implicit methods, Crank-Nicolson method. System of ordinary differential equations 15. Week Convergence, stability and consistency analysis of the methods 16. Week Final Exam |
Sources
Course Book | 1. 1. Numerical Solution of Partial Differential Equations by K.W. Morton and D.F. Mayers, Cambridge University Press, 1994. 2.Numerical Analysis of Differential Equations by A. Iserles, Cambridge University Press, 1996. |
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Other Sources | 2. 1.Computer Methods for ODEs and Differential-Algebraic Equations by U.M. Ascher & L.R. Petzold, SIAM, 1998. 2.Numerical Solution of Partial Differential Equations: Finite Difference Methods by G.D. Smith, Clarendon Press, Oxford, 1985. |
Evaluation System
Requirements | Number | Percentage of Grade |
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Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 5 | 30 |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 1 | 30 |
Final Exam/Final Jury | 1 | 40 |
Toplam | 7 | 100 |
Percentage of Semester Work | |
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Percentage of Final Work | 100 |
Total | 100 |
Course Category
Core Courses | X |
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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 | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Gains the ability to apply advanced computational and/or manufacturing technology knowledge to solve manufacturing engineering problems. | |||||
2 | Develops the ability to analyze and define issues related to manufacturing technologies. | |||||
3 | Develops an approach for solving encountered engineering problems, and designs and conducts models and experiments. | |||||
4 | Designs and manufactures a comprehensive manufacturing system —including method, product, or device development— based on the creative application of fundamental engineering principles, under constraints of economic viability, environmental sustainability, and manufacturability. | |||||
5 | Selects and uses modern techniques and engineering tools for manufacturing engineering applications. | |||||
6 | Conducts scientific research in the field of manufacturing engineering and/or plans and carries out a project involving innovative manufacturing technologies. | |||||
7 | Effectively uses information technologies to collect and analyze data, think critically, interpret results, and make sound decisions. | |||||
8 | Works effectively as a member of multidisciplinary and intra-disciplinary teams or individually; demonstrates the confidence and organizational skills required. | X | ||||
9 | Communicates effectively in both spoken and written Turkish and English. | |||||
10 | Engages in lifelong learning, accesses information, keeps up with the latest developments in science and technology, and continuously renews oneself. | |||||
11 | Demonstrates awareness and a sense of responsibility regarding professional, legal, ethical, occupational safety, and social issues in the field of Manufacturing Engineering. | |||||
12 | Effectively utilizes resources (personnel, equipment, costs) to enhance national competitiveness and improve manufacturing industry productivity; conducts solution-oriented project and risk management; and demonstrates awareness of entrepreneurship, innovation, and sustainable development. | |||||
13 | Gathers knowledge about the health, environmental, social, and legal impacts of engineering practices at both global and local levels when making decisions. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 2 | 32 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | 5 | 5 | 25 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 8 | 16 |
Prepration of Final Exams/Final Jury | 1 | 10 | 10 |
Total Workload | 131 |