SDU Education Information System
   Home   |  Login Türkçe  | English   
 
   
 
 


 
Course Information
Course Unit Title : Advanced Technologies and Applications in Energy Systems
Course Unit Code : 01MAE5155
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : Preb
Semester : 255.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants : ---
Learning Outcomes of The Course Unit : 1) To recognize alternative heating and cooling systems
2) To learn alternative refrigerants
3) Applicability to energy systems new methods such as artificial neural networks, fuzzy logic, genetic algorithm
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : Applicability of new methods such as artificial neural networks, fuzzy logic, genetic algorithm to cooling, heating, air conditioning, solar energy systems, modeling of complex energy systems with these new techniques, optimization, completing the missing data in energy systems.
Languages of Instruction : Turkish
Course Goals : 1) To present alternative heating and cooling systems
2) To teach alternative refrigerants
3) To apply new methods such as artificial neural networks, fuzzy logic, genetic algorithm to energy systems
Course Aims : Using of intelligent systems in energy systems.
WorkPlacement   Not Available
Recommended or Required Reading
Textbook : There is not
Additional Resources : Artificial intelligence in thermal systems design: concepts and applications, Enrico Sciubba, Roberto Melli.Nova Science Publishers, Inc, ISBN 1-560-72599-0, 274p, New York, 1998.
Material Sharing
Documents : There is not
Assignments : There is not
Exams : There is not
Additional Material : There is not
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 3 42  
Homeworks :
2 20 40  
Presentation :
0 0 0  
Project :
1 20 20  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
1 15 15  
Finals :
1 15 15  
Workload Hour (30) :
30  
Total Work Charge / Hour :
174  
Course's ECTS Credit :
6      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 70
Quiz :
0 0
Homework :
1 20
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
1 10
Workshop :
0 0
Seminary :
0 0
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Global warming and energy consumption.
  Study Materials: Getting the course syllabus
2 International and national environment legalizations.
  Study Materials: Reading of current literature
3 The meaning of the alternative heating and cooling systems.
  Study Materials: Reading of current literature
4 Alternative refrigerants.
  Study Materials: Research about alternative refrigerants.
5 Transcritical cooling cycles.
  Study Materials: Research about systems with R744 refrigerant.
6 Determining of optimum working parameters of alternative cooling systems.
  Study Materials: Reading of current literature
7 Absorption cooling systems.
  Study Materials: Reading of current literature
8 Heat pump systems.
  Study Materials: Reading of current literature
9 The designs of the heat pump systems.
  Study Materials: Investigation of sample applications.
10 Gas engine driven heat pumps.
  Study Materials: Reading of current literature.
11 Radiant heating and cooling systems.
  Study Materials: Reading of current literature.
12 Introduction to second law efficiencies of heating and cooling systems.
  Study Materials: Reading of current literature.
13 Application of new methods such as artificial neural networks, fuzzy logic, genetic algorithm to energy systems
  Study Materials: Sample applications
14 Application of new methods such as artificial neural networks, fuzzy logic, genetic algorithm to energy systems
  Study Materials: Sample applications