GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
ADVANCED NUMERICAL ANALYSIS/5021334
Course Title: ADVANCED NUMERICAL ANALYSIS
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
Students attending this course will able to gain ability for numerical differentiation and numerical integration.
Students attending this course will able to gain ability for numerical solution of ordinary and partial differential equations

 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Solution of non-linear systems of equations, interpolation-extrapolation
2. Week  Numerical differentiation.
3. Week  Numerical integration, Simpson’s rule, Gauss Quadrature, multiple integral.
4. Week  Ordinary differential equations, Numerical solution of initial value problems, Euler method, Taylor series method.
5. Week  Numerical solution of initial value problems, Taylor series method.
6. Week  Numerical solution of initial value problems, Runge-kutta method.
7. Week  Boundary value problems, shooting method.
8. Week  Midterm exam, Application of boundary value problems, finite difference method
9. Week  Finite difference method for boundary value problems, applications
10. Week  Partial-differential equations, Numerical solution of elliptic partial-differential equations, finite difference method, dirichlet and neumann bounda
11. Week  Numerical solution of elliptic partial-differential equations, hybrid method, ADI method, applications
12. Week  Numerical solution of parabolic partial-differential equations, explicit method, implicit method.
13. Week  Numerical solution of parabolic partial-differential equations, crank-nicolson method, theta method, derivative boundary conditions.
14. Week  Numerical solution of hyperbolic partial-differential equations.
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
1
10
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
1
10
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
10
5
50
 Searching in Internet and Library
8
7
56
 Material Design and Implementation
0
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
20
20
 Final Exam and Preperation for Final Exam
1
20
20
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Based on the qualifications of the undergraduate level, reaching and expanding the knowledge by conducting scientific research in the field of Automotive Engineering, evaluating, interpreting and applying the informationX
2To have comprehensive knowledge about current techniques and methods applied in Automotive Engineering and their limitationsX
3Completing and applying knowledge by scientific methods using limited or missing data; to use information from different disciplines togetherX
4Ability to be aware of new and developing applications of the profession, to learn them when necessary and to use their technologies effectivelyX
5An ability to design and solve engineering problems in the field of Automotive EngineeringX
6Developing new and / or original ideas and methods related to the field of Automotive Engineering; Ability to develop innovative solutions in system, component or process designsX
7Designing and applying analytical, modeling and experimental based research in the field of Automotive Engineering; ability to analyze and interpret complex situations encountered in this processX
8Ability to control and lead by taking into consideration social, scientific and ethical values in the stage of data collection in order to solve the problems related to the field of Automotive EngineeringX
9Ability to transfer the process and results of his / her studies in written and verbal form in a systematic and clear manner in national and international environments within or outside the fieldX
10Compliance with social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activitiesX
11Awareness of entrepreneurship and innovation and knowledge of sustainable developmentX
12To have information about the effects of engineering applications on health, environment and safety in global and social dimensionsX
13Awareness of the legal consequences of engineering solutionsX
 -- NAME OF LECTURER(S)
   (Prof. Dr. Can ÇINAR)
 -- WEB SITE(S) OF LECTURER(S)
   (http://websitem.gazi.edu.tr/site/cancinar)
 -- EMAIL(S) OF LECTURER(S)
   (cancinar@gazi.edu.tr)