IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v263y2023ipbs0360544222026202.html
   My bibliography  Save this article

Crude rubber seed oil esterification using a solid catalyst: Optimization by hybrid adaptive neuro-fuzzy inference system and response surface methodology

Author

Listed:
  • Jisieike, Chiazor Faustina
  • Ishola, Niyi Babatunde
  • Latinwo, Lekan M.
  • Betiku, Eriola

Abstract

Esterifying high free fatty acid (FFA) oil with acid is necessary to avoid soap formation during biodiesel production. Thus, this study evaluated the efficacies of response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) in modeling the esterification process for crude rubber seed oil (CRSO) with a high FFA catalyzed by dehydrated Fe2(SO4)3. A central composite design (CCD) with three factors and five levels was applied to examine the influence of methanol:CRSO molar ratio (25:1–75:1), Fe2(SO4)3 loading (8–16 wt %), and time (3–4 h) on reduction of the high FFA (22.2%) of CRSO. The performance of the particle swarm optimization (PSO), genetic algorithm (GA), and RSM were assessed in optimizing the process variables. Statistics for the ANFIS and RSM models showed that both could reliably describe the esterification process with low mean relative percent deviation (MRPD) of 1.77 and 4.98; and high coefficients of determination (R2) of 0.9838 and 0.9730, respectively. The optimization results are in this order: ANFIS-PSO, ANFIS-GA, RSM-PSO, RSM, and RSM-GA. The ANFIS-PSO hybrid predicted the best optimal condition as Fe2(SO4)3 loading of 16.97 wt%, methanol:CRSO molar ratio of 44.21:1, and time of 3.39 h with the lowest FFA of 0.56%.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222026202
    DOI: 10.1016/j.energy.2022.125734
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222026202
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125734?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Thangarasu, Vinoth & M, Angkayarkan Vinayakaselvi & Ramanathan, Anand, 2021. "Artificial neural network approach for parametric investigation of biodiesel synthesis using biocatalyst and engine characteristics of diesel engine fuelled with Aegle Marmelos Correa biodiesel," Energy, Elsevier, vol. 230(C).
    2. Chia-Chi Chang & Syuan Teng & Min-Hao Yuan & Dar-Ren Ji & Ching-Yuan Chang & Yi-Hung Chen & Je-Lueng Shie & Chungfang Ho & Sz-Ying Tian & Cesar Augusto Andrade-Tacca & Do Van Manh & Min-Yi Tsai & Mei-, 2018. "Esterification of Jatropha Oil with Isopropanol via Ultrasonic Irradiation," Energies, MDPI, vol. 11(6), pages 1-15, June.
    3. Dhawane, Sumit H. & Kumar, Tarkeshwar & Halder, Gopinath, 2016. "Biodiesel synthesis from Hevea brasiliensis oil employing carbon supported heterogeneous catalyst: Optimization by Taguchi method," Renewable Energy, Elsevier, vol. 89(C), pages 506-514.
    4. Can, Özer & Baklacioglu, Tolga & Özturk, Erkan & Turan, Onder, 2022. "Artificial neural networks modeling of combustion parameters for a diesel engine fueled with biodiesel fuel," Energy, Elsevier, vol. 247(C).
    5. Petković, Dalibor & Barjaktarovic, Miljana & Milošević, Slaviša & Denić, Nebojša & Spasić, Boban & Stojanović, Jelena & Milovancevic, Milos, 2021. "Neuro fuzzy estimation of the most influential parameters for Kusum biodiesel performance," Energy, Elsevier, vol. 229(C).
    6. Betiku, Eriola & Akintunde, Aramide Mistura & Ojumu, Tunde Victor, 2016. "Banana peels as a biobase catalyst for fatty acid methyl esters production using Napoleon's plume (Bauhinia monandra) seed oil: A process parameters optimization study," Energy, Elsevier, vol. 103(C), pages 797-806.
    7. 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).
    8. Betiku, Eriola & Okunsolawo, Samuel S. & Ajala, Sheriff O. & Odedele, Olatunde S., 2015. "Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tr," Renewable Energy, Elsevier, vol. 76(C), pages 408-417.
    9. Mostafaei, Mostafa & Javadikia, Hossein & Naderloo, Leila, 2016. "Modeling the effects of ultrasound power and reactor dimension on the biodiesel production yield: Comparison of prediction abilities between response surface methodology (RSM) and adaptive neuro-fuzzy," Energy, Elsevier, vol. 115(P1), pages 626-636.
    10. Anietie O. Etim & Eriola Betiku & Sheriff O. Ajala & Peter J. Olaniyi & Tunde V. Ojumu, 2018. "Potential of Ripe Plantain Fruit Peels as an Ecofriendly Catalyst for Biodiesel Synthesis: Optimization by Artificial Neural Network Integrated with Genetic Algorithm," Sustainability, MDPI, vol. 10(3), pages 1-15, March.
    11. Ramadhas, A.S. & Jayaraj, S. & Muraleedharan, C., 2005. "Characterization and effect of using rubber seed oil as fuel in the compression ignition engines," Renewable Energy, Elsevier, vol. 30(5), pages 795-803.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Arévalo, Paul & Cano, Antonio & Jurado, Francisco, 2024. "Large-scale integration of renewable energies by 2050 through demand prediction with ANFIS, Ecuador case study," Energy, Elsevier, vol. 286(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olatundun, Esther Adedayo & Borokini, Omowumi Oluwatumininu & Betiku, Eriola, 2020. "Cocoa pod husk-plantain peel blend as a novel green heterogeneous catalyst for renewable and sustainable honne oil biodiesel synthesis: A case of biowastes-to-wealth," Renewable Energy, Elsevier, vol. 166(C), pages 163-175.
    2. Muhammad, Gul & Potchamyou Ngatcha, Ange Douglas & Lv, Yongkun & Xiong, Wenlong & El-Badry, Yaser A. & Asmatulu, Eylem & Xu, Jingliang & Alam, Md Asraful, 2022. "Enhanced biodiesel production from wet microalgae biomass optimized via response surface methodology and artificial neural network," Renewable Energy, Elsevier, vol. 184(C), pages 753-764.
    3. Babatunde Oladipo & Tunde V Ojumu & Lekan M Latinwo & Eriola Betiku, 2020. "Pawpaw ( Carica papaya ) Peel Waste as a Novel Green Heterogeneous Catalyst for Moringa Oil Methyl Esters Synthesis: Process Optimization and Kinetic Study," Energies, MDPI, vol. 13(21), pages 1-25, November.
    4. Pirmoradi, Neda & Ghaneian, Mohammad Taghi & Ehrampoush, Mohammad Hassan & Salmani, Mohammad Hossein & Hatami, Behnam, 2021. "The conversion of poultry slaughterhouse wastewater sludge into biodiesel: Process modeling and optimization," Renewable Energy, Elsevier, vol. 178(C), pages 1236-1249.
    5. Eldiehy, Khalifa S.H. & Gohain, Minakshi & Daimary, Niran & Borah, Doljit & Mandal, Manabendra & Deka, Dhanapati, 2022. "Radish (Raphanus sativus L.) leaves: A novel source for a highly efficient heterogeneous base catalyst for biodiesel production using waste soybean cooking oil and Scenedesmus obliquus oil," Renewable Energy, Elsevier, vol. 191(C), pages 888-901.
    6. Christopher Tunji Oloyede & Simeon Olatayo Jekayinfa & Abass Olanrewaju Alade & Oyetola Ogunkunle & Opeyeolu Timothy Laseinde & Ademola Oyejide Adebayo & Adeola Ibrahim Abdulkareem & Ghassan Fadhil Sm, 2023. "Synthesis of Biobased Composite Heterogeneous Catalyst for Biodiesel Production Using Simplex Lattice Design Mixture: Optimization Process by Taguchi Method," Energies, MDPI, vol. 16(5), pages 1-26, February.
    7. Aghbashlo, Mortaza & Hosseinpour, Soleiman & Tabatabaei, Meisam & Dadak, Ali, 2017. "Fuzzy modeling and optimization of the synthesis of biodiesel from waste cooking oil (WCO) by a low power, high frequency piezo-ultrasonic reactor," Energy, Elsevier, vol. 132(C), pages 65-78.
    8. Nath, Biswajit & Kalita, Pranjal & Das, Bipul & Basumatary, Sanjay, 2020. "Highly efficient renewable heterogeneous base catalyst derived from waste Sesamum indicum plant for synthesis of biodiesel," Renewable Energy, Elsevier, vol. 151(C), pages 295-310.
    9. Aliakbari, Karim & Ebrahimi-Moghadam, Amir & Pahlavanzadeh, Mohammadsadegh & Moradi, Reza, 2023. "Performance characteristics and exhaust emissions of a single-cylinder diesel engine for different fuels: Experimental investigation and artificial intelligence network," Energy, Elsevier, vol. 284(C).
    10. Daimary, Niran & Boruah, Pankaj & Eldiehy, Khalifa S.H. & Pegu, Tapan & Bardhan, Pritam & Bora, Utpal & Mandal, Manabendra & Deka, Dhanapati, 2022. "Musa acuminata peel: A bioresource for bio-oil and by-product utilization as a sustainable source of renewable green catalyst for biodiesel production," Renewable Energy, Elsevier, vol. 187(C), pages 450-462.
    11. Subramonia Pillai, N. & Kannan, P. Seeni & Vettivel, S.C. & Suresh, S., 2017. "Optimization of transesterification of biodiesel using green catalyst derived from Albizia Lebbeck Pods by mixture design," Renewable Energy, Elsevier, vol. 104(C), pages 185-196.
    12. Patchimpet, Jaran & Simpson, Benjamin K. & Sangkharak, Kanokphorn & Klomklao, Sappasith, 2020. "Optimization of process variables for the production of biodiesel by transesterification of used cooking oil using lipase from Nile tilapia viscera," Renewable Energy, Elsevier, vol. 153(C), pages 861-869.
    13. Daabo, Ahmed M. & Saeed, Liqaa I. & Altamer, Marwa H. & Fadhil, Abdelrahman B. & Badawy, Tawfik, 2022. "The production of bio-based fuels and carbon catalysts from chicken waste," Renewable Energy, Elsevier, vol. 201(P1), pages 21-34.
    14. Ahmad Abbaszadeh-Mayvan & Barat Ghobadian & Gholamhassan Najafi & Talal Yusaf, 2018. "Intensification of Continuous Biodiesel Production from Waste Cooking Oils Using Shockwave Power Reactor: Process Evaluation and Optimization through Response Surface Methodology (RSM)," Energies, MDPI, vol. 11(10), pages 1-13, October.
    15. M.H.H. Ishak & Farzad Ismail & Sharzali Che Mat & M.Z. Abdullah & M.S. Abdul Aziz & M.Y. Idroas, 2019. "Numerical Analysis of Nozzle Flow and Spray Characteristics from Different Nozzles Using Diesel and Biofuel Blends," Energies, MDPI, vol. 12(2), pages 1-25, January.
    16. 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.
    17. Iftikhar Ahmad & Adil Sana & Manabu Kano & Izzat Iqbal Cheema & Brenno C. Menezes & Junaid Shahzad & Zahid Ullah & Muzammil Khan & Asad Habib, 2021. "Machine Learning Applications in Biofuels’ Life Cycle: Soil, Feedstock, Production, Consumption, and Emissions," Energies, MDPI, vol. 14(16), pages 1-27, August.
    18. Bahman Najafi & Sina Faizollahzadeh Ardabili & Amir Mosavi & Shahaboddin Shamshirband & Timon Rabczuk, 2018. "An Intelligent Artificial Neural Network-Response Surface Methodology Method for Accessing the Optimum Biodiesel and Diesel Fuel Blending Conditions in a Diesel Engine from the Viewpoint of Exergy and," Energies, MDPI, vol. 11(4), pages 1-18, April.
    19. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    20. Mahmudul, H.M. & Hagos, F.Y. & Mamat, R. & Adam, A. Abdul & Ishak, W.F.W. & Alenezi, R., 2017. "Production, characterization and performance of biodiesel as an alternative fuel in diesel engines – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 497-509.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222026202. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.