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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao International Journa...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
International Journal of Energy Research
Article . 2022 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Performance improvement of co‐culture inoculated microbial fuel cell using fuzzy modelling and Harris hawks optimization

Authors: Hegazy Rezk; Enas Taha Sayed; Mohammad Ali Abdelkareem; A. G. Olabi;

Performance improvement of co‐culture inoculated microbial fuel cell using fuzzy modelling and Harris hawks optimization

Abstract

SummaryMicrobial fuel cell (MFC) is a promising technology since two important processes: wastewater treatment and electrical energy, can be obtained simultaneously. The performance of the MFC (maximum power density (MPD) and COD removal) depends mainly on substrate concentration, pH time, and initial COD. Therefore, the main target of this work is to simultaneously increase the MPD and COD removal by determining the optimal controlling parameters. The proposed methodology integrates fuzzy modelling and Harris Hawks optimization (HHO). Firstly, based on the experimental data set, an accurate fuzzy model is created to simulate the performance of MFC in terms of four controlling parameters. To prove the superiority of fuzzy model, the results are compared with response surface methodology (RSM) in terms of RMSE and coefficient of determination (R2). Secondly, using HHO, the optimal values of substrate concentration, co‐culture composition, pH, and time are determined. These four controlling parameters are used as decision variables during the optimization process, whereas the objective function is the simultaneous maximization of the MPD and COD removal. The obtained results proved that the optimal substrate concentration, pH, time, and initial COD values are 58.2%, 7, 14.4 days, and 32 × 10−3 (mg/L) respectively. Under this condition, the integration between fuzzy and HHO, the overall performance of MFC has been improved by 10.37% and 19.13%, respectively, compared with the experimental and RSM.

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