Prediction of Surface Quality in Electrical Discharge Machining Process for 7024 AL Alloy Using Artificial Neural Network Model | ||
Anbar Journal of Engineering Sciences | ||
Article 13, Volume 13, Issue 2, November 2022, Pages 106-113 PDF (804.03 K) | ||
Document Type: Research Paper | ||
DOI: 10.37649/aengs.2022.176364 | ||
Authors | ||
safaa kadhim* 1; Khalida Kadhim Mansor2; Mohanad Qusay Abbood2 | ||
1Production Engineering and Metallurgy Department, University of Technology, Baghdad, iraq | ||
2Department of Production Engineering and Metallurgy / University of Technology / Iraq | ||
Abstract | ||
In this article, an experimental study of the single-pass hybrid (PV/T) collector is conducted in the climatic conditions of Fallujah city, where the experimental results are compared with a previous research to validate the results. The effect of changing the angle of inclination of the hybrid collector (PV/T) and its effect on the electrical power in the range (20°-50°) is studied. The optimum angle of the collector is found to be 30°, which gives a maximum electrical power of 58.8 W at average solar radiation of 734.35 W/m2. In another experimental study with different air flow rates ranged from 0.04 kg/s to 0163 kg/s, where it is found that the maximum electrical power of 57.66 W at an air flow rate of 0.135 kg/s, while the maximum thermal efficiency reaches 33.53% at an air flow of 0.163 kg/s at average solar radiation of 786 W/m2. | ||
Keywords | ||
Surface Roughness; electrical discharge; Artificial Neural Network Model | ||
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