Syllabus ( ENVE 538 )
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Basic information
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| Course title: |
Optimization and Numerical Methods in Environmental Engineering |
| Course code: |
ENVE 538 |
| Lecturer: |
Assoc. Prof. Dr. Murat EYVAZ
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| ECTS credits: |
7.5 |
| GTU credits: |
3 (3+0+0) |
| Year, Semester: |
1/2, Fall and Spring |
| Level of course: |
Second Cycle (Master's) |
| Type of course: |
Area Elective
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| Language of instruction: |
Turkish
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| Mode of delivery: |
Face to face
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| Pre- and co-requisites: |
None |
| Professional practice: |
No |
| Purpose of the course: |
The students are expected to gain the ability to use optimization techniques and numerical methods in environmental engineering problems. |
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Learning outcomes
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Upon successful completion of this course, students will be able to:
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Define basic optimization concepts and solve equations.
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Environmental Engineering
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Formulate, construct and use methods and experiments at advanced level to solve environmental problems and interpret and synthesize their results
Method of assessment
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Written exam
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Use optimization techniques to solve optimization problems that they encounter in their own work.
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Environmental Engineering
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Review the literature critically pertaining to his/her research projects, and connect the earlier literature to his/her own results
Method of assessment
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Written exam
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Use available appropriate software for optimization.
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Environmental Engineering
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Develop an awareness of continuous learning in relation with modern technology
Method of assessment
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Written exam
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Understand the optimization applications related to environmental engineering in literature.
Contribution to Program Outcomes
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Define and manipulate advanced concepts of Environmental Engineering
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Formulate, construct and use methods and experiments at advanced level to solve environmental problems and interpret and synthesize their results
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Demonstrate awareness for the social impacts of solutions to advanced problems
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Find out new methods to improve his/her knowledge.
Method of assessment
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Written exam
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Contents
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| Week 1: |
Basic concepts in optimization, solution of engineering problems |
| Week 2: |
Error analysis and obtaining of meaningful data |
| Week 3: |
Equations in engineering applications |
| Week 4: |
Solution of linear equations |
| Week 5: |
One-dimensional unconstrained optimization |
| Week 6: |
Multidimensional unconstrained optimization |
| Week 7: |
Midterm exam |
| Week 8: |
Constrained optimization |
| Week 9: |
Reactor design with minimal cost |
| Week 10: |
Wastewater treatment plant design with minimal cost |
| Week 11: |
Curve fitting and interpolation |
| Week 12: |
Linear regression and population models |
| Week 13: |
Boundary value problems and applications |
| Week 14: |
Finite element method and applications |
| Week 15*: |
An overview |
| Week 16*: |
Final Exam |
| Textbooks and materials: |
Introduction to Operations Research, Hillier F.S., Lieberman, G.J., McGrawHill, 2000. |
| Recommended readings: |
Optimization in Operations Research, Rardin, R.L., 1998. |
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* Between 15th and 16th weeks is there a free week for students to prepare for final exam.
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Assessment
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| Method of assessment |
Week number |
Weight (%) |
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| Mid-terms: |
7 |
30 |
| Other in-term studies: |
14, 15 |
20 |
| Project: |
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0 |
| Homework: |
4, 8, 12 |
15 |
| Quiz: |
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0 |
| Final exam: |
16 |
35 |
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Total weight: |
(%) |
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Workload
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| Activity |
Duration (Hours per week) |
Total number of weeks |
Total hours in term |
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| Courses (Face-to-face teaching): |
3 |
14 |
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| Own studies outside class: |
4 |
14 |
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| Practice, Recitation: |
0 |
0 |
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| Homework: |
6 |
6 |
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| Term project: |
10 |
2 |
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| Term project presentation: |
6 |
1 |
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| Quiz: |
0 |
0 |
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| Own study for mid-term exam: |
10 |
1 |
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| Mid-term: |
3 |
1 |
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| Personal studies for final exam: |
10 |
1 |
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| Final exam: |
3 |
1 |
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Total workload: |
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Total ECTS credits: |
* |
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* ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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