Chemical Engineering Department discuss M.Sc.
Chemical Engineering Department discuss M.Sc. thesis entitled: "Prediction of Refrigeration System Performance Using the Artificial Neural Network Approach"
The thesis of the student (Ayad Lafta Majeed) aimed to reach a technique that can be relied upon to predict the performance of cooling systems based on parameters and conditions similar to those on the basis of which this technology was designed. The components of the system with eight output parameters are (coefficient of performance of the cooling system, cooling capacity, volumetric flow of coolant, deep cooling, roasting temperature, consumed energy, volumetric efficiency of the compressor and temperature reference ratio (HRR).
The researcher concluded that the designed ANN algorithm had a very high predictive rate, as the most important determinants of its accuracy were the mean square error MSE was 3.6 * 10^_5. And the correlation coefficient R is 0.9996 and it was very close to the practical data that was recorded from the laboratory device (refrigeration system). The preliminary results obtained from this technique indicate that increasing the performance coefficient of the cooling system and reducing energy consumption if - the higher the evaporator temperature and the lower the compressibility ratio.
The discussion committee consisted of:-
- Assist.Prof. Qassem Saleh Mahdi /the head.
- Assist. Prof. Ahmed Abdel-Nabi/ member.
- Lec. Dr. Ali Daoud /member.
- Prof. Dr. Ahmed A. Mohamed / supervisor.
- Assist. Prof. Dr. Alaa A. Jaber / supervisor.
