GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
NUMERICAL METHODS IN ACCIDENT ANALYSIS/5441322
Course Title: NUMERICAL METHODS IN ACCIDENT 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
-Gaining ability to use numerical methods for the solution of different kinds investigation problem.
-Mathematical Modelling of accident investigation problems and development of solution strategies using numerical methods.
-Computer programming applications using numerical methods in accident investigation problems

 -- MODE OF DELIVERY
   The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  1.Introduction Mathematical Modelling, Error Analysis, Programming
2. Week  2. Roots of Non-Linear Equations,
3. Week  3. Solutions of Non-linear Eqs. Systems
4. Week  4. Linear Algebraic Equations: Gauss Elimination, Gauss-Seidel, Gauss-Jordan, Thomas Algorithm,L-U Decomposition
5. Week  5. Least-Squares Regression; Linear Regression, Multiple Linear Regression, Nonlinear Regression.
6. Week  6.Interpolation; Newton's Divided-Difference Interpolating, Polynomials, Lagrange Interpolating Polynomials.:
7. Week  7.Numerical Differentiation and Integration
8. Week  8. Midterm Examination 1
9. Week  9. Improper Integrals, Numerical Differentiation, High-Accuracy Differentiation Formulas, Partial Differentiation.
10. Week  10. Ordinary Differential Equations: Euler's Method, Improved Euler (Heun) Method,
11. Week  11. Ordinary Differential Equations: Runge-Kutta Methods.
12. Week  12. Solution of Systems of Ordinary Differential Equations.
13. Week  13. Solution Methods for Partial Differential Equations.
14. Week  14. Case Studies for Partial Differential Equations.
15. Week  Midterm Examination 2
16. Week  Final Examination
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
2
40
 Assignment
1
10
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
50
 Percentage of Final Exam to Total Score  
50
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
13
3
39
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
13
3
39
 Searching in Internet and Library
13
3
39
 Material Design and Implementation
0
0
0
 Report Preparing
13
2
26
 Preparing a Presentation
0
0
0
 Presentation
0
0
0
 Midterm Exam and Preperation for Midterm Exam
2
15
30
 Final Exam and Preperation for Final Exam
1
20
20
 Other (should be emphasized)
0
0
0
 TOTAL WORKLOAD: 
193
 TOTAL WORKLOAD / 25: 
7.72
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Course develops and deepens student’s knowledge in the field of expertise based on his / her undergraduate qualifications.X
2Grasping the interaction between disciplines related to the field.X
3The ability to use the expert-level theoretical and practical knowledge acquired in his field.X
4Interpreting and forming new types of knowledge by combining the knowledge from the area and the knowledge from various other disciplines.X
5Solves the issues of his field by using scientific methods.X
6The ability to carry out a study that requires expertise in the field independently.X
7Developing new strategic approaches to solve the unforeseen and complex problems arising in the practical processes.X
8Producing solutions by considering social and environmental dimensions in the applications in the field.X
9Taking the initiative in environments that require solving problems related to the field.X
10Evaluates the information in a critical way and encourages learning.X
11Transferring the current developments in the field and his/her own studies in written, oral, and visual forms.X
12Ability to develop social relations and the norms directing these relations critically and the ability to transform them when necessary.X
13Having proficiency in a foreign language and establishing written and oral communication with that language.X
14Uses computer software required by the field.X
15Uses information and communication technologies at an advanced level required by the field.X
16Collects data related to the field, reviews and makes conclusions; implements and shares them by considering ethical values.X
17Develops different perspectives related to the field, plans them and assesses them within the quality framework.X
18Internalizes the knowledge gained in the field, transforms it into a skill and uses it with interdisciplinary studies.X
 -- NAME OF LECTURER(S)
   (Head of Department)
 -- WEB SITE(S) OF LECTURER(S)
   (Ana Bilim Dalı Başkanlığı)
 -- EMAIL(S) OF LECTURER(S)
   (kazalar@gazi.edu.tr)