ECTS - Finite Difference Methods for PDEs

Finite Difference Methods for PDEs (MATH524) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Finite Difference Methods for PDEs MATH524 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Technical Electives (Group A)
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Question and Answer, Problem Solving.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This graduate course is designed to give students in applied mathematics the expertise necessary to understand, construct and use finite difference methods for the numerical solution of partial differential equations. The emphasis is on implementation of various finite difference schemes to some model partial differential equations, finding numerical solutions, evaluating numerical results and understands how and why results might be good or bad based on consistency, stability and convergence of finite difference scheme.
Course Learning Outcomes The students who succeeded in this course;
  • Choose and apply suitable finite difference methods for numerical solutions of partial differential equations encountered in science and engineering
  • Discuss finite difference methods with respect to stability, convergence and consistency with a reasonable degree of mathematical rigor
  • Solve linear systems arising from finite difference solutions of partial differential equations.
  • Write and implement computer programs for the numerical solutions of partial differential equations by finite difference method.
Course Content Finite difference method, parabolic equations: explicit and implicit methods, Richardson, Dufort-Frankel and Crank-Nicolson schemes; hyperbolic equations: Lax-Wendroff, Crank-Nicolson, box and leap-frog schemes; elliptic equations: consistency, stability and convergence of finite different methods for numerical solutions of partial differential equ

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 -Classification of Partial Differential Equations (PDE): Parabolic, Hyperbolic and Elliptic PDE. -Boundary conditions. -Finite difference methods, Finite difference operators [Lapidus] p:1-3, 12, 13, 28-30, 34-41, [Smith] p.1-8
2 Parabolic equations: -Explicit methods -Truncation error, consistence, order of accuracy [Morton & Mayers] p.10-16
3 -Convergence of the explicit schemes. -Stability by Fourier analysis and matrix method [Morton & Mayers] p.16-22 [Smith] p.60-64
4 -Implicit methods. -Thomas algorithm -Richardson scheme [Morton & Mayers] p.22-26,38, 39
5 -Duforth-Frankel’s explicit scheme -Boundary conditions, [Smith] p.32-40,94 [Morton & Mayers] p. 39-42
6 -Crank-Nicolson implicit scheme and its stability -Iterative methods for solving implicit scheme s [Smith].p.17-20, 64-67, 24-32,
7 -Finite difference methods for variable coefficient PDE. [Morton & Mayers] p.46-51,54-56
8 Hyperbolic equations: -The upwind scheme and its local truncation error, stabilirty and convergence. -The Courant, Friedrichs and Lewy (CLF) condition. [Morton & Mayers] p:89-95
9 -The Lax-Wendroff scheme and its stability -The Crank-Nicolson scheme and its stability [Morton & Mayers] p.100, [ Strikwerda] p.63, 77
10 Midterm Exam
11 -The box scheme and its order of accuracy -The Leap-frog scheme and its stability [Morton & Mayers] p.116-118, 123,124
12 Elliptic equations: -A model problem:Poisson equation -Boundary conditions on a curve boundary [Morton & Mayers] p.194,195, 199-203
13 -Basic iterative schemes [Morton & Mayers] p.237-244
14 -Alternating Direction Implicit method [Smith] p.151-153
15 Review
16 Final Exam

Sources

Course Book 1. K.W. Morton, D.F. Mayers, Numerical Solutions of Partial Differential Equations, 2nd Edition, Cambridge University Press, 2005.
Other Sources 2. G.D. Smith, Numerical Solutions of Partial Differential Equations, Oxford University Press, 1969
3. L. Lapidus, G.F. Pinder, Numerical Solutions of Partial Differential Equations in Science and Engineering, John Wiley & Sons, Inc. 1999.
4. J.C. Strikwerda, Finite Difference Schemes and Partial Differential Equations, 2nd Edition, SIAM, 2004

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 4 20
Presentation 1 10
Project 1 10
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 30
Toplam 8 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses
Major Area Courses X
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 Accumulated knowledge on mathematics, science and mechatronics engineering; an ability to apply the theoretical and applied knowledge of mathematics, science and mechatronics engineering to model and analyze mechatronics engineering problems. X
2 An ability to differentiate, identify, formulate, and solve complex engineering problems; an ability to select and implement proper analysis, modeling and implementation techniques for the identified engineering problems. X
3 An ability to design a complex system, product, component or process to meet the requirements under realistic constraints and conditions; an ability to apply contemporary design methodologies; an ability to implement effective engineering creativity techniques in mechatronics engineering. (Realistic constraints and conditions may include economics, environment, sustainability, producibility, ethics, human health, social and political problems.) X
4 An ability to develop, select and use modern techniques, skills and tools for application of mechatronics engineering and robot technologies; an ability to use information and communications technologies effectively.
5 An ability to design experiments, perform experiments, collect and analyze data and assess the results for investigated problems on mechatronics engineering and robot technologies.
6 An ability to work effectively on single disciplinary and multi-disciplinary teams; an ability for individual work; ability to communicate and collaborate/cooperate effectively with other disciplines and scientific/engineering domains or working areas, ability to work with other disciplines.
7 An ability to express creative and original concepts and ideas effectively in Turkish and English language, oral and written.
8 An ability to reach information on different subjects required by the wide spectrum of applications of mechatronics engineering, criticize, assess and improve the knowledge-base; consciousness on the necessity of improvement and sustainability as a result of life-long learning; monitoring the developments on science and technology; awareness on entrepreneurship, innovative and sustainable development and ability for continuous renovation.
9 Be conscious on professional and ethical responsibility, competency on improving professional consciousness and contributing to the improvement of profession itself.
10 A knowledge on the applications at business life such as project management, risk management and change management and competency on planning, managing and leadership activities on the development of capabilities of workers who are under his/her responsibility working around a project.
11 Knowledge about the global, societal and individual effects of mechatronics engineering applications on the human health, environment and security and cultural values and problems of the era; consciousness on these issues; awareness of legal results of engineering solutions.
12 Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions.
13 Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planing, improving or changing the norms with a criticism.
14 A competency on developing strategy, policy and application plans on the mechatronics engineering and evaluating the results in the context of qualitative processes.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 2 28
Presentation/Seminar Prepration 1 8 8
Project 1 7 7
Report
Homework Assignments 4 3 12
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 12 12
Total Workload 125