COURSE UNIT TITLE

: NUMERICAL AND APPROXIMATE METHODS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MAT 5102 NUMERICAL AND APPROXIMATE METHODS ELECTIVE 3 0 0 9

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ŞENNUR SOMALI

Offered to

Computer Engineering Non-Thesis
PHYSICS
Mineral Processing
COASTAL ENGINEERING
MARINE CHEMISTRY
Ph.D. in Biotechnology
COMPUTER ENGINEERING
Statistics
M.Sc. in Biochemistry
MARINE GEOLOGY AND GEOPHYSICS
PHYSICAL OCEANOGRAPHY
NATURAL BUILDING STONES AND GEMSTONES
PHYSICS
Environmental Engineering
Computer Science
Applied Geology
STATISTICS
ENVIRONMENTAL EARTH SCIENCES
GEOGRAPHICAL INFORMATION SYSTEMS - NON THESIS (EVENING PROGRAM)
Biomedical Tehnologies (English)
Industrial Ph.D. Program In Advanced Biomedical Technologies
GEOGRAPHICAL INFORMATION SYSTEMS
Industrial Ph.D. Program In Advanced Biomedical Technologies
Economic Geology
NAVAL ARCHITECTURE
Computer Engineering Non-Thesis
Mineral Processing
Computer Engineering
Mining Operation
MARINE LIVING RESOURCES
MARINE LIVING RESOURCES
MARINE CHEMISTRY
ENVIRONMENTAL EARTH SCIENCES-NON THESIS
Geothermal Energy
Mining Operation
Chemistry
Mathematics
COASTAL ZONE MANAGEMENT
UNDERWATER ARCHAELOGY
EARTHQUAKE MANAGEMENT - NON THESIS
Economic Geology
Mathematics
ENVIRONMENTAL ENGINEERING
Ph.D. in Computer Science
Ph.D. in Biotechnology
M.Sc. Textile Engineering
Textile Engineering
NAVAL ARCHITECTURE
EARTHQUAKE MANAGEMENT
M.Sc. Geothermal Energy (Non-Thesis-Evening)
GEOGRAPHIC INFORMATION SYSTEMS
Statistics
Chemistry
Textile Engineering
COASTAL ENGINEERING
Mining Operation
Geographical Information Systems (Non-Thesis)
Mineral Processing
Applied Geology
ENGINEERING MANAGEMENT- NON THESIS (EVENING PROGRAM)
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM)
Ph.D in Biochemistry
Computer Engineering
Ph.D. in Occupational Health and Safety
MARINE GEOLOGY AND GEOPHYSICS
Chemistry
Occupational Healty and Safety
BIOTECHNOLOGY
Logistics Engineering

Course Objective

This course aims to give an introduction to numerical methods for engineering problems

Learning Outcomes of the Course Unit

1   Will be able to adopt the concept of error, converge and stability.
2   Will be able to find exact or approximate solution of equations.
3   Will be able to find exact or approximate solution of system of equations.
4   Will be able to find a nearest curve to a function that lies on a different space.
5   Will be able to solve Numeriacal Differentiation and Integration
6   Will be able to understand the algorithms for solving initial value problems or boundary value problems of ordinary differential equations.
7   Will be able to understand the algorithms for solving partial differential equations.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Computational and Mathematical Preliminaries
2 Newton's method for non-linear systems
3 The solution of linear systems: Direct methods
4 The solution of linear systems: Error Analysis and Norms
5 The solution of linear systems: Iterative methods
6 The solution of linear systems: Algebraic Eigenvalue Problem
7 Midterm
8 Curve Fitting: The method of Least Squares
9 Curve Fitting: Fourier Series and Trigonometric Polynomials
10 Numerical Solutions of ODEs: Initial Value Problems
11 Numerical Solutions of ODEs: Boundary Value Problems
12 Numerical Solutions of PDEs: Hyperbolic Equations
13 Numerical Solution of PDEs: Parabolic Equations
14 Numerical Solution of PDEs: Elliptic Equations

Recomended or Required Reading

John H. Mathews ''Numerical Methods for Mathematics, Science and Engineering''. Prentice-Hall. 1992.

Planned Learning Activities and Teaching Methods

Lecture notes, Presentation, Problem solving

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE MTE * 0.50 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

Attending at least 70 percent of lectures is mandatory.

Contact Details for the Lecturer(s)

meltem.adiyaman@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 8 104
Preparation for midterm exam 1 35 35
Preparation for final exam 1 35 35
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 219

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.1
LO.233
LO.34
LO.43
LO.5
LO.64
LO.7