Advanced System Simulation (MDES650) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Advanced System Simulation MDES650 Elective Courses 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 Elective Courses
Course Level Natural & Applied Sciences Master's Degree
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 An ability to access, analyze and evaluate the knowledge needed for the solution of advanced chemical engineering and applied chemistry problems.
2 An ability to self-renewal by following scientific and technological developments within the philosophy of lifelong learning.
3 An understanding of social, environmental, and the global impacts of the practices and innovations brought by chemistry and chemical engineering.
4 An ability to perform original research and development activities and to convert the achieved results to publications, patents and technology.
5 An ability to apply advanced mathematics, science and engineering knowledge to advanced engineering problems.
6 An ability to design and conduct scientific and technological experiments in lab- and pilot-scale, and to analyze and interpret their results.
7 Skills in design of a system, part of a system or a process with desired properties and to implement industry.
8 Ability to perform independent research.
9 Ability to work in a multi-disciplinary environment and to work as a part of a team.
10 An understanding of the professional and occupational responsibilities.

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