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| Course Description |
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| Course Name |
: |
Advanced Wastewater Treatment |
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| Course Code |
: |
CEV418 |
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| Course Type |
: |
Compulsory |
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| Level of Course |
: |
First Cycle |
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| Year of Study |
: |
4 |
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| Course Semester |
: |
Spring (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Assoc.Prof.Dr. ÇAĞATAYHAN BEKİRERSU
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| Learning Outcomes of the Course |
: |
Understand environmental modeling principles
Learn what kinds of data are needed to generate a model input file, in general
Understand the factors and processes that effect dissolved oxygen concentration in receiving waters
Understand general characteristics of streams and rivers
Gain the ability to apply dissolved oxygen and BOD analyses in streams and rives
Understand general characteristics of lakes
Gain the ability to apply dissolved oxygen and BOD analyses in lakes
Understand general characteristics of estuaries and gain the ability to apply dissolved oxygen and BOD analyses in estuaries
Gain the ability to run a water quality model and evaluate the results
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| Mode of Delivery |
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Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
The aim is to define the processes used for eliminating the colloidal and dissolved items present in the triditional secondary tratment and give the details on design. |
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| Course Contents |
: |
Introduction to modeling, Fundamentals of mathematical modeling, Examples of analytical and mathematical methods, Water quality modeling in lakes and rivers, Introduction to modeling software, Building environmental models. |
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| Language of Instruction |
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Turkish |
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| Work Place |
: |
Classroom |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
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1 |
Introduction/Orientation |
None. |
Face-to-Face |
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2 |
Introduction to modeling |
None. |
Face-to-Face |
|
3 |
Fundamentals of mathematical modeling |
None. |
Face-to-Face |
|
4 |
Fundamentals of mathematical modeling |
None. |
Face-to-Face |
|
5 |
Examples of analytical and mathematical methods |
None. |
Face-to-Face |
|
6 |
Examples of analytical and mathematical methods |
None. |
Face-to-Face |
|
7 |
General characterstics of lakes and factors affecting the water quality of lakes |
None. |
Face-to-Face, visuals |
|
8 |
Water quality modeling in lakes |
None. |
Face-to-Face, visuals |
|
9 |
Mid-term exam |
None. |
Written exam in the classroom |
|
10 |
General characterstics of rivers and factors affecting the water quality of rivers |
None. |
Face-to-Face, visuals |
|
11 |
Water quality modeling in rivers |
None. |
Face-to-Face, visuals |
|
12 |
General characteristics of estuarines and factors affecting the water quality of estuarines |
None. |
Face-to-Face, visuals |
|
13 |
Introduction to modeling software |
None. |
Face-to-Face, visuals |
|
14 |
Building environmental models |
None. |
Face-to-Face, visuals |
|
15 |
Case studies |
None. |
Face-to-Face, visuals |
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16/17 |
Final exam |
None. |
Written exam in the classroom |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
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| |
| Required Course Material(s) |
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|
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
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Mid-term Exams (Written, Oral, etc.) |
1 |
70 |
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Homeworks/Projects/Others |
1 |
30 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
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Final Assessments
|
100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
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1 |
Becomes equipped with adequate knowledge in mathematics, science, environment and engineering sciences |
5 |
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2 |
Becomes able to apply theoretical knowledge in mathematics, science, environment and engineering sciences |
5 |
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3 |
Determines, describes, formulates and gains capabilities in solving engineering problems |
5 |
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4 |
Analyzes a system, components of the system or process, gains the designing capabilities of the system under the real restrictive conditions. |
4 |
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5 |
Chooses ans uses the ability to apply modern tools and design technics, suitable analytical methods, modeling technics for the engineering applications |
3 |
|
6 |
Designs and performs experiments, data collection, has the ability of analyzing results |
1 |
|
7 |
Works individually and in inter-disciplinary teams effectively |
3 |
|
8 |
Becomes able to reach knowledge and for this purpose does literature research and to uses data base and other information sources |
5 |
|
9 |
Becomes aware of the necessity of lifelong learning and continuously self renewal |
2 |
|
10 |
Capable of effective oral and written skills in at least one foreign language for technical or non-technical use |
1 |
|
11 |
Effective use of Information and communication technologies |
4 |
|
12 |
Professional and ethical responsibility |
2 |
|
13 |
Project management, workplace practices, environmental and occupational safety; awareness about the legal implications of engineering applications |
1 |
|
14 |
Becomes aware of universal and social effects of engineering solutions and applications, entrepreneurship and innovation and to have idea of contemporary issues |
2 |
|
15 |
Defines necessities in learning in scientific, social, cultural and artistic areas and improves himself/herself accordingly. |
1 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
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Class Time (Exam weeks are excluded) |
13 |
3 |
39 |
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Out of Class Study (Preliminary Work, Practice) |
13 |
5 |
65 |
| Assesment Related Works |
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Homeworks, Projects, Others |
1 |
20 |
20 |
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Mid-term Exams (Written, Oral, etc.) |
1 |
10 |
10 |
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Final Exam |
1 |
15 |
15 |
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Total Workload: | 149 |
| Total Workload / 25 (h): | 5.96 |
| ECTS Credit: | 6 |
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