Course Name: CSE 511 Introduction to Computational Science 

Degree:  MS and PhD

Code

Year/Semester

Local Credits

ECTS Credits

Course Implementation, Hours/Week

Course

Tutorial

Laboratory

CSE 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++)

Course Category by Content, %

Basic Sciences

Engineering Science

Engineering Design

Humanities

80

20

Course Description

This course has two major topics:

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

Course Objectives

This course provides a core of mathematics to all applied and computational sciences and an introduction to the concept of computational programming languages for scientific modelling and computation.

Course Learning Outcomes

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

1. understand important aspects of computational science and engineering
2. understand and apply fundamental numerical methods within computational sciences
3. be able to combine principles of computer-based modelling and numerical analysis with scientific computing
4. develop algorithms and implement simulation by using computational programming languages in the field of mathematical modeling
5. formulate innovative, effective, and creative computational and mathematical approaches for scientific and engineering problems

Instructional Methods and Techniques

Books, lecture notes and related computer programming tools

Tutorial Place

Class and Laboratory

Co-term Condition

Textbook

Stephen Lynch, Dynamical Systems with Applications using Mathematica, Birkhauser Boston, 2007

Other References

1. Stephen Lynch, Dynamical Systems with Applications using MATLAB, Birkhäuser, 2004
2. Steven H. Strogatz, Nonlinear Dynamics and Chaos: with applications to Physics, Biology, Chemistry, and Engineering, Perseus Books Publishing, 1994
3. E. Ott, Chaos in Dynamical Systems, Cambridge, 2002
4. Ali H. Nayfeh, B. Balachandran, Applied Nonlinear Dynamics: Analytical, Computational, and Experimental Methods, Wiley, 2004

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

187.525

Course ECTS Credits

7,5

Week

Topics

Course Outcomes

1

Introduction to computational science

I-II-III-IV-V

2

Approximations in scientific computation and computer arithmetic

I-II

3

Systems of linear equations

I-II

4

Systems of nonlinear equations

I-II

5

Planar systems, interacting species, limit cycles

I-II-III

6

Introduction to programming languages

II-III-IV

7

Introducing the computing packages widely used in applied sciences

II-III-IV-V

8

Midterm

9

Scientific programming in applied sciences

IV-V

10

Advanced scientific programming in applied sciences

I-II-III-IV-V

11

Chaotic dynamics and applications, bifurcation theory, local and global bifurcations

I-II-III-IV-V

12

Three-dimensional autonomous systems and chaos

I-II-III-IV-V

13

Introduction to research in computational science

I-II-III-IV-V

14

Applications in computational science

I-II-III-IV-V

Program Outcomes

Level of Contribution

1

2

3

a

Knowledge of the fundamentals of numerical simulation and modeling with computational tools and techniques

X

b

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

X

c

Understanding of the theoretical basis of computer science to identify, formulate, and solve progressively more challenging computational science problems

X

d

Ability to develop and apply computational solving strategies appropriately in scientific and engineering problems

X

e

Ability to use and apply computer science principles to linear/nonlinear dynamical systems that give rise to real world problems

X

f

Ability to model and analyze dynamical systems in mathematics, physics, chemistry, biology, material science and other branches of engineering problems

X

g

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

X

h

Ability to design and implement a computer-based system or develop a program to meet the criteria in industry

X

Prepared by

 Dr. Orhan Özgür AYBAR

Date

5/02/2018

Signature