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Application of adaptive neuro-fuzzy inference system and response surface methodology in biodiesel synthesis from jatropha–algae oil and its performance and emission analysis on diesel engine coupled with generator

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  • Kumar, Sunil
  • Jain, Siddharth
  • Kumar, Harmesh

Abstract

Present study presents the results of methyl esters preparation from Jatropha-Algae oil using transesterification process. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and the response surface methodology (RSM) based Box–Behnken techniques were used for modelling and analysis of different parameters viz molar ratio, temperature, reaction time, and catalyst concentration in biodiesel production process. Significant regression model with R2value of 0.9867 was obtained under a molar ratio of 6–12, KOH of 0–2% w/w, time of 60–180 min and temperature of 35–55 °C using RSM. The ANFIS model was used to individually correlate the output variable (biodiesel yield) with four input variables with R2 value of 0.9998. Finally, a study investigating the performance and emissions of a diesel engine fuelled with biodiesel blends (B0, B5, B10 and B20 vol%) has been performed concluding significant reduction of emission.

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  • Kumar, Sunil & Jain, Siddharth & Kumar, Harmesh, 2021. "Application of adaptive neuro-fuzzy inference system and response surface methodology in biodiesel synthesis from jatropha–algae oil and its performance and emission analysis on diesel engine coupled ," Energy, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:energy:v:226:y:2021:i:c:s0360544221006770
    DOI: 10.1016/j.energy.2021.120428
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    1. Silitonga, A.S. & Masjuki, H.H. & Ong, Hwai Chyuan & Sebayang, A.H. & Dharma, S. & Kusumo, F. & Siswantoro, J. & Milano, Jassinnee & Daud, Khairil & Mahlia, T.M.I. & Chen, Wei-Hsin & Sugiyanto, Bamban, 2018. "Evaluation of the engine performance and exhaust emissions of biodiesel-bioethanol-diesel blends using kernel-based extreme learning machine," Energy, Elsevier, vol. 159(C), pages 1075-1087.
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    1. Rezk, Hegazy & Inayat, Abrar & Abdelkareem, Mohammad A. & Olabi, Abdul G. & Nassef, Ahmed M., 2022. "Optimal operating parameter determination based on fuzzy logic modeling and marine predators algorithm approaches to improve the methane production via biomass gasification," Energy, Elsevier, vol. 239(PB).
    2. Siddharth Jain, 2023. "An Assessment of the Operation and Emission Characteristics of a Diesel Engine Powered by a New Biofuel Prepared Using In Situ Transesterification of a Dry Spirogyra Algae–Jatropha Powder Mixture," Energies, MDPI, vol. 16(3), pages 1-16, February.
    3. Jisieike, Chiazor Faustina & Ishola, Niyi Babatunde & Latinwo, Lekan M. & Betiku, Eriola, 2023. "Crude rubber seed oil esterification using a solid catalyst: Optimization by hybrid adaptive neuro-fuzzy inference system and response surface methodology," Energy, Elsevier, vol. 263(PB).

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