Study of Multiple Half Blades Effect on the Performance of Savonius Rotor: Experimental Study and Artificial Neural Network (ANN) Model

Mohanad Al Ghriybah; H uuml seyin  Ccedil amur; Mohd Fadhli Zulkafli; Muhammad Abid Khan; Youssef Kassem; and Engin Esenel

doi:10.17485/ijst/2018/v11i38/129966

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Study of Multiple Half Blades Effect on the Performance of Savonius Rotor: Experimental Study and Artificial Neural Network (ANN) Model

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2018/v11i38/129966

Year: 2018, Volume: 11, Issue: 38, Pages: 1-12

Original Article

Study of Multiple Half Blades Effect on the Performance of Savonius Rotor: Experimental Study and Artificial Neural Network (ANN) Model

Mohanad Al-Ghriybah¹ , Hüseyin Çamur² ,Mohd Fadhli Zulkafli¹ , Muhammad Abid Khan^2*, Youssef Kassem^2,3 and Engin Esenel²

¹ Department of Aeronautical Engineering, Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), 86400 Parit Raja, Batu Pahat, Johor, Malaysia; [email protected], [email protected]
² Faculty of Engineering, Department of Mechanical Engineering, Near East University, Nicosia-99138, Cyprus; [email protected], [email protected], [email protected]
³ Faculty of Civil and Environmental Engineering, Department of Civil Engineering, Near East University, Nicosia-99138, Cyprus; [email protected]

^*Author for correspondence
Muhammad Abid Khan,
Faculty of Engineering, Department of Mechanical Engineering, Near East University, Nicosia-99138, Cyprus; [email protected], [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objectives: To estimate and compare the performance in terms of torque and mechanical power of a new configuration of Savonius rotors with the conventional one. Methods/Statistical Analysis: New configuration comprises multiple half blades added to conventional configuration. Two different new configurations with different half blade geometries and locations were designed. The torque and mechanical power of the rotor was measured experimentally at various wind speeds and rotor positions. The tests were done 4-6 times for each measurement and the results were averaged. Moreover, the measured data were predicted using Artificial Neural Network (ANN). Findings: The location of half blades effect the performance of the rotor. Additionally, both new configurations of Savonius rotors are associated with above 45% increase in mechanical power compared to the conventional Savonius wind turbine. Based on the simulated results, it is found that the R2 value within a range of 0.902-0.99, which indicated a very good fit of the measured data with the calculated data. Application/Improvements: ANN technique can be applied as a powerful tool and effective way in predicting and assessing the performance of the rotor (torque and mechanical power).

Keywords: ANN, Experimental Study, Multiple Half Blades, Performance, Savonius Rotor