Back

Scientific Computing: Numerical Methods

PİRİ REİS UNIVERSITY

GRADUATE SCHOOLS OF SCIENCE AND ENGINEERING

Computational Science and Engineering Programme

Course catalog Form

 

Course Name: Scientific Computing: Numerical Methods

Degree:  MS and PhD

 

Code

 

 

Year/Semester

 

Local Credits

 

ECTS Credits

 

Course Implementation, Hours/Week

Course

Tutorial

Laboratory

MATH 511

1/1 (fall)

3

7.5

3

-

-

Department

Computational Science and Engineering

Instructors

 

Dr. Orhan Özgür AYBAR

Contact Information

 

E-mail: oaybar@pirireis.edu.tr

Office Hours

 

Web page

http://www.pirireis.edu.tr

Course Type

 Compulsory

Course Language

English

Course Prerequisites

  Introductory programming languages level (C/C++) and MATLAB

Course Category by Content, %

Basic Sciences

Engineering Science

Engineering Design

Humanities

70

30

 

 

Course Description

This course has two major topics:

  1. Numerical calculations in Applied mathematics (linear algebra, numerical analysis and differential equations for engineering and applied sciences)
  2. Numerical Methods (applications in mathematics, physics, biology and engineering)

 

Course Objectives

 

This course provides solutions by using numerical methods to the  applied and computational sciences

 

Course Learning Outcomes

 

On successful completion of this course, students will be able to

  1. understand the numerical methods in applied sciences
  2. understand and apply fundamental numerical methods within computational sciences
  3. develop algorithms and implement simulation by using symbolic computation in the field of applied sciences

Instructional Methods and Techniques

Books, lecture notes and related computer programming tools

Tutorial Place

Class and Laboratory

Co-term Condition

 

Textbook

Numerical Methods in Engineering with MATLAB, Jaan Kiusalaas, cambridge university press, 2005.

Other References

Applied Numerical Methods Using MATLAB, Won Young Yang, Wenwu Cao, Tae-Sang Chung, John Morris, JOHN WILEY & SONS, INC., PUBLICATION, 2005.

Homework & Projects

Homework assignments based on lectures will be given regularly

Laboratory Work

Computer programs of the topics covered in the class will be regularly developed in the computer lab projects

Computer Use

Programming Languages (C, C++, Mathematica, Matlab, Maple)

Other Activities

The weekly coverage may change as it depends on the progress

 

Assessment Criteria

Activities

Quantity

Effects on Grading, %

Attendance

 

 

Midterm

1

30

Quiz

 

 

Homework

 

 

Term Paper/Project

 

 

Laboratory Work

1

20

Practices

 

 

Tutorial

 

 

Seminar

 

 

Presentation

 

 

Field Study

 

 

Final Exam

1

50

TOTAL

 

100

Effects of Midterm on Grading, %

 

50

Effects of Final on Grading, %

 

50

TOTAL

 

100

 

ECTS/

WORKLOAD TABLE

Activities

Count

Hours

Total Workload

Lecture

14

3

42

Midterm

1

50

50

Quiz

 

 

 

Homework

 

 

 

Term Paper/Project

 

 

 

Laboratory Work

15

3.5

52.5

Practices

 

 

 

Tutorial

 

 

 

Seminar

 

 

 

Presentation

 

 

 

Field Study

 

 

 

Final Exam

1

43

43

Total Workload

 

 

187.5

Total Workload/25

 

 

187.5/25

Course ECTS Credits

 

 

7,5

 

Week

 

Topics

Course Outcomes

1

Introduction to numerical methods

I-II-III

2

Systems of Linear Algebraic Equations

I-II

3

Interpolation and Curve Fitting

I-II

4

Roots of Equations

I-II

5

Numerical Differentiation

I-II-III

6

Numerical Integration

I-II-III

7

Initial Value Problems

I-II-III

8

Midterm

 

9

Two-Point Boundary Value Problems

I-II-III

10

Symmetric Matrix Eigenvalue Problems I

I-II-III

11

Symmetric Matrix Eigenvalue Problems II

I-II-III

12

Introduction to Optimization

I-II-III

13

Nonlinear Equations, Ordinary and Partial Differential Equations

I-II-III

14

Applications in computational science (Symbolic Computation)

I-II-III

 

Relationship between the Course and the Computational Science and Engineering Curriculum

 

 

 

Program Outcomes

Level of Contribution

1

2

3

a

Repeats the current techniques and methods applied in the field of technology and their limitations, effects and results.

 

 

X

b

Completes and implements knowledge with scientific methods using limited or incomplete data; integrates knowledge of different disciplines.

 

 

 

X

c

Models and applies experimental studies and solves complex situations in the process.

 

 

 

X

d

Leads in multidisciplinary teams in the field of technology.

 

 

X

 

e

Uses the methods and software used in the field of technology and communication technologies  at advanced level.

 

 

 

X

f

Observes social, scientific and ethical values in the collection, interpretation, application and announcement phases of data in all professional activities.

 

 

X

 

g

Understanding the role of computer science and computational methods for solving or approximating the solution of advanced computational science problems

 

 

X

h

Ability to develop algorithms and computational approaches to solve the investigated dynamical system and accomplish mathematical analyses using an appropriate programming language

 

 

X

         1: Small, 2: Partial, 3: Full

Prepared by

 

Dr. Orhan Özgür AYBAR

Date

 

05/02/2018

Signature