Investigation of thermal performance of SAC variables using fuzzy logic based expert system

Abstract

The thermal performance of a solar air collector (SAC) is investigated experimentally under the different climatic conditions of north eastern India using fuzzy logic based expert system (FLES). The FLES based on subtractive clustering (SC) with the fuzzy logic method where here, SC is used for extraction of optimal fuzzy IF-THEN rules while a fuzzy logic is used for modeling of SAC variables. This work considered four input variables [like mass flow rate (m), collector tilt angles (θ), solar radiation (Q), temperature (T)] and the four output variables [i.e. efficiency (η), exergetic efficiency (ηII), temperature rise (∆T), and pressure drop (∆P)]. First, 272 trials of experimentation on SAC are performed by varying m from 0.0078 to 0.0118 kg/s and θ from 30 to 60°, whereas the variation of metrological data is obtained in different working days. Then modeling and parametric analysis is carried out for SAC. Experimental results reveal that the value of η increases with the increase in m, Q, T and θ up to 45°. The higher value of m results in a higher value of ∆P and that reduces the value of ηII. Also, FLES model provides comparable and acceptable values for SAC. At last, validation of the FLES model is done via published data to confirm the results.