GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
NUMERICAL METHODS IN FLUID MECHANICS/5191310
Course Title: NUMERICAL METHODS IN FLUID MECHANICS
Credits 3 ECTS 7.5
Semester 1 Compulsory/Elective Elective
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Prof. Dr. Haşmet TÜRKOĞLU
 -- WEB SITE(S) OF LECTURER(S)
  www.websitem.gazi.edu.tr/site/hasmet
 -- EMAIL(S) OF LECTURER(S)
  hasmet@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
Knowledge of basic steps of computational solution of flow problems.
Discritization of basic equations and boundary conditions of flow problems.
Formulation and programing of methods used for solution of set of algebraic equations.
Formulation and programing of algorithms used for solution of flow problems.
 -- MODE OF DELIVERY
  The mode of delivery of this course is in class instruction and problem solution, homework assingment and limitted experimental application.
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  There is no recommended optional programme component for this course.
 --COURSE CONTENT
1. Week  INTRODUCTION: Definitions, methods of analysis, fundamental laws.
2. Week  INTRODUCTION: Governing equations, conservation of mass, momentum and energy equations.
3. Week  DISCRETIZATION METHODS: Finite difference, finite volume, finite element and spectral methods
4. Week  SOLUTION OF LINEAR ALGEBRAIC EQUATIONS: Direct methods, Gauss elimination method, Gauss Jordan elimination method, iterative methods.
5. Week  HEAT CONDUCTION: One-dimensional unsteady heat conduction equation, explicit, implicit and Crank-Nicholson formulations
6. Week  HEAT CONDUCTION: Two and three-dimensional heat conduction equations
7. Week  HEAT CONDUCTION: Solution of algebraic equations, overrelaxation and underrelaxation
8. Week  MIDTERM EXAM I
9. Week  CONVECTION DIFFUSION EQUATION: Steady, one-dimensional convection diffusion equation, exact solution, upwind, hybrid and Power-Law Formulation.
10. Week  CONVECTION DIFFUSION EQUATION: General formulation, comparison of different methods.
11. Week  CONVECTION DIFFUSION EQUATION: Two- and three-dimensional flows.
12. Week  SOLUTION OF TWO- AND THREE DIMENSIONAL NAVIER-STOKES EQUATIONS: Primitive variable method, SIMPLE and SIMLER algorithms.
13. Week  MIDTERM EXAM II
14. Week  SOLUTION OF TWO-DIMENSIONAL NAVIER-STOKES EQUATION: Stream function- vorticity method.
15. Week  SOLUTION OF TWO-DIMENSIONAL NAVIER-STOKES EQUATION: Stream function- vorticity method.
16. Week  FINAL EXAM
 -- RECOMMENDED OR REQUIRED READING
  S. V. Patankar, 1980, Numerical Heat Transfer and Fluid Flow, Hemisphere Publishing Corporation. H. K. Versteeg and W. Malalasekera, 1995, An Introduction to Computational Fluid Dynamics, Prentice Hall. D. A. Anderson, J. C. Tannehill, Richard H. Plecther, 1984, Computational Fluid Mechanics and Heat Transfer.
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  -
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
2
40
 Assignment
6
20
 Exercises
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
60
 Contribution of Final Examination to Overall Grade  
40
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
3
42
 Practising Hours of Course Per Week
0
 Reading
12
4
48
 Searching in Internet and Library
12
4
48
 Designing and Applying Materials
0
 Preparing Reports
8
4
32
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
1
10
10
 Final and Studying for Final
1
10
10
 Other
0
 TOTAL WORKLOAD: 
190
 TOTAL WORKLOAD / 25: 
7.6
 ECTS: 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Ability to access wide and deep information with scientific researches in the field of Engineering, evaluate, interpret and implement the knowledge gained in his/her field of studyX
2Ability to complete and implement “limited or incomplete data” by using the scientific methods.X
3Ability to consolidate engineering problems, develop proper method(s) to solve and apply the innovative solutions to themX
4Ability to develop new and original ideas and method(s), to develop new innovative solutions at design of system, component or processX
5Gain comprehensive information on modern techniques, methods and their borders which are being applied to engineeringX
6Ability to design and apply analytical, modelling and experimental based research, analyze and interpret the faced complex issues during the design and apply processX
7Gain high level ability to define the required information and dataX
8Ability to work in multi-disciplinary teams and to take responsibility to define approaches for complex situationsX
9Systematic and clear verbal or written transfer of the process and results of studies at national and international environmentsX
10Aware of social, scientific and ethical values guarding adequacy at all professional activities and at the stage of data collection, interpretation, and announcementX
11Aware of new and developing application of profession and ability to analyze and study on those applicationsX
12Ability to interpret engineering application’s social and environmental dimensions and it’s compliance with the social environmentX