ECTS - Advanced System Simulation

Advanced System Simulation (MDES650) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Advanced System Simulation MDES650 3 0 0 3 5
Pre-requisite Course(s)
An introductory statistics course having a comparable content to IE 220.
Course Language English
Course Type N/A
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives The course intends to give a background of simulation for modeling complex engineering systems. The students are directed to practical work concerning their specific field of research based on this foundation.
Course Learning Outcomes The students who succeeded in this course;
  • To provide students a working knowledge of simulation theory and applications. To understand and apply advanced concepts of simulation to complex engineering problems. To emphasize the application areas of simulation.
Course Content Discrete simulation models for complex systems, input probability distributions, random variable generation, statistical inferences, variance reduction, continuous processes, verification and validation, advanced models.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction (definitions and types of simulations) Related pages of the other sources
2 Discrete simulation models and their mechanisms for complex systems Related pages of the other sources
3 Statistical methods for selecting input probability distributions, generating random variables Related pages of the other sources
4 Making statistical inferences from simulation results Related pages of the other sources
5 Variance reduction techniques, experimental design. Related pages of the other sources
6 Case study I Related pages of the other sources
7 Modeling continuous processes Related pages of the other sources
8 Modeling continuous processes Related pages of the other sources
9 Verification and validation of simulation models Related pages of the other sources
10 Case study II Related pages of the other sources
11 Multivariate data analysis-Time series analysis-Forecasting Related pages of the other sources
12 Advanced methods for simulation. Related pages of the other sources
13 Advanced methods for simulation Related pages of the other sources
14 Case study III-Future perspectives in simulation. Related pages of the other sources
15 Overall review -
16 Final exam -

Sources

Course Book 1. -
Other Sources 2. [1] Simulation Modeling and Analysis, 4Ed., Law, McGraw-Hill, New York, 2000.
3. [2] Kelton, D., R. Sadowski, and D. Sturrock, Simulation with Arena, McGraw-Hill, 3rd edition, 2003.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory 1 10
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 4 20
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 2 40
Final Exam/Final Jury 1 30
Toplam 8 100
Percentage of Semester Work 70
Percentage of Final Work 30
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to carry out advanced research activities, both individual and as a member of a team X
2 Ability to evaluate research topics and comment with scientific reasoning X
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics X
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions X
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems X
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level X
7 Contribute scientific and technological advancements on engineering domain of his/her interest area X
8 Contribute industrial and scientific advancements to improve the society through research activities X

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory 1 2 2
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project
Report
Homework Assignments 4 8 32
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 2 4 8
Prepration of Final Exams/Final Jury 1 10 10
Total Workload 132