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Information
| Unit | FACULTY OF ENGINEERING |
| ENVIRONMENTAL ENGINEERING PR. | |
| Code | CMS347 |
| Name | System Analysis |
| Term | 2018-2019 Academic Year |
| Semester | 5. Semester |
| Duration (T+A) | 2-0 (T-A) (17 Week) |
| ECTS | 4 ECTS |
| National Credit | 2 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. BELGİN BAYAT |
| Course Instructor |
Prof. Dr. BELGİN BAYAT
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Understanding basic and importance of optimization techniques in the field of environmental applications. Gaining knowledge on optimization methods. Having ability to solve environmental problems in the area of water pollution, waste management,air pollution control usinglinear programming. Gaining knowledge on economical analysis techniques and economic analysis of environmental projects.
Course Content
System approach, Mathematical models and optimization, Introduction to optimization algorithm: Lagrange multipliers, Linear programming: Graphical and Simplex method, Introduction to engineering economics, Economic comparison methods
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explanation of benefits of optimization techniques and application approaches |
| LO02 | Description of system approaches |
| LO03 | Linear programming methods and solving environmental problems using this techniques |
| LO04 | Explanation of principals of economy in environmental engineering applications,interpretation of effect of time on economy |
| LO05 | Explanation of economic comparison methods |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Becomes equipped with adequate knowledge in mathematics, science, environment and engineering sciences | 5 |
| PLO02 | - | Becomes able to apply theoretical knowledge in mathematics, science, environment and engineering sciences | 5 |
| PLO03 | - | Determines, describes, formulates and gains capabilities in solving engineering problems | 5 |
| PLO04 | - | Analyzes a system, components of the system or process, gains the designing capabilities of the system under the real restrictive conditions. | 5 |
| PLO05 | - | Chooses ans uses the ability to apply modern tools and design technics, suitable analytical methods, modeling technics for the engineering applications | 5 |
| PLO06 | - | Designs and performs experiments, data collection, has the ability of analyzing results | 5 |
| PLO07 | - | Works individually and in inter-disciplinary teams effectively | 4 |
| PLO08 | - | Becomes able to reach knowledge and for this purpose does literature research and to uses data base and other information sources | 5 |
| PLO09 | - | Becomes aware of the necessity of lifelong learning and continuously self renewal | 4 |
| PLO10 | - | Capable of effective oral and written skills in at least one foreign language for technical or non-technical use | 3 |
| PLO11 | - | Effective use of Information and communication technologies | 4 |
| PLO12 | - | Defines necessities in learning in scientific, social, cultural and artistic areas and improves himself/herself accordingly. | 3 |
| PLO13 | - | Professional and ethical responsibility | 4 |
| PLO14 | - | Project management, workplace practices, environmental and occupational safety; awareness about the legal implications of engineering applications | 3 |
| PLO15 | - | Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation and to have idea of contemporary issues | 3 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | System approach | Lecture notes | |
| 2 | Mathematical models and optimization, | Lecture notes | |
| 3 | Introduction to optimization algorithm: Lagrange multipliers, | Lecture notes | |
| 4 | Introduction to optimization algorithm: Lagrange multipliers, | Lecture notes | |
| 5 | Linear programming: Graphical method, | Lecture notes | |
| 6 | Linear programming: Simplex method | Lecture notes | |
| 7 | Linear programming: Simplex method, | Lecture notes | |
| 8 | Mid-Term Exam | Lecture notes | |
| 9 | Midterm exam | Lecture notes | |
| 10 | Introduction to engineering economics | Lecture notes | |
| 11 | Introduction to engineering economics | Lecture notes | |
| 12 | Economic comparison methods | Lecture notes | |
| 13 | Economic comparison methods | Lecture notes | |
| 14 | Economic comparison methods | Lecture notes | |
| 15 | Solving problems | Lecture notes | |
| 16 | Term Exams | ||
| 17 | Term Exams |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 2 | 28 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 2 | 28 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 8 | 8 |
| Final Exam | 1 | 24 | 24 |
| Total Workload (Hour) | 88 | ||
| Total Workload / 25 (h) | 3,52 | ||
| ECTS | 4 ECTS | ||