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Response Surface Methodology and Artificial Neural Networks-Based Yield Optimization of Biodiesel Sourced from Mixture of Palm and Cotton Seed Oil

Author

Listed:
  • Luqman Razzaq

    (Department of Mechanical Engineering, University of Gujrat, Gujrat 50700, Pakistan)

  • Muhammad Mujtaba Abbas

    (Department of Mechanical, Mechatronics and Manufacturing Engineering (New Campus), University of Engineering and Technology (UET), Lahore 54000, Pakistan)

  • Sajjad Miran

    (Department of Mechanical Engineering, University of Gujrat, Gujrat 50700, Pakistan)

  • Salman Asghar

    (Department of Product and Industrial Design (PID), University of Engineering and Technology (UET), Lahore 54890, Pakistan)

  • Saad Nawaz

    (Department of Mechanical, Mechatronics and Manufacturing Engineering (New Campus), University of Engineering and Technology (UET), Lahore 54000, Pakistan)

  • Manzoore Elahi M. Soudagar

    (Department of Mechanical Engineering, School of Technology, Glocal University, Delhi-Yamunotri Marg, SH-57, Mirzapur Pole 247121, Uttar Pradesh, India
    Department of Mechanical Engineering, University Centre for Research & Development, Chandigarh University, Mohali 140413, Punjab, India)

  • Nabeel Shaukat

    (Graduate School of Advance Sciences and Engineering, Hiroshima University, Hiroshima 739-8511, Japan)

  • Ibham Veza

    (Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, Melaka 76100, Malaysia)

  • Shahid Khalil

    (Mechanical Engineering Technology, National Skills University, Islamabad 44000, Pakistan)

  • Anas Abdelrahman

    (Department of Mechanical Engineering, Faculty of Engineering & Technology, Future University in Egypt, New Cairo 11845, Egypt)

  • Muhammad A. Kalam

    (Faculty of Engineering and IT, University of Technology, Sydney 2007, Australia)

Abstract

In this present study, cold flow properties of biodiesel produced from palm oil were improved by adding cotton seed oil into palm oil. Three different mixtures of palm and cotton oil were prepared as P50C50, P60C40, and P70C30. Among three oil mixtures, P60C40 was selected for biodiesel production via ultrasound assisted transesterification process. Physiochemical characteristics—including density, viscosity, calorific value, acid value, and oxidation stability—were measured and the free fatty acid composition was determined via GCMS. Response surface methodology (RSM) and artificial neural network (ANN) techniques were utilized for the sake of relation development among operating parameters (reaction time, methanol-to-oil ratio, and catalyst concentration) ultimately optimizing yield of palm–cotton oil sourced biodiesel. Maximum yield of P60C40 biodiesel estimated via RSM and ANN was 96.41% and 96.67% respectively, under operating parameters of reaction time (35 min), M:O molar ratio (47.5 v / v %), and catalyst concentration (1 wt %), but the actual biodiesel yield obtained experimentally was observed 96.32%. The quality of the RSM model was examined by analysis of variance (ANOVA). ANN model statistics exhibit contented values of mean square error (MSE) of 0.0001, mean absolute error (MAE) of 2.1374, and mean absolute deviation (MAD) of 2.5088. RSM and ANN models provided a coefficient of determination (R 2 ) of 0.9560 and a correlation coefficient (R) of 0.9777 respectively.

Suggested Citation

  • Luqman Razzaq & Muhammad Mujtaba Abbas & Sajjad Miran & Salman Asghar & Saad Nawaz & Manzoore Elahi M. Soudagar & Nabeel Shaukat & Ibham Veza & Shahid Khalil & Anas Abdelrahman & Muhammad A. Kalam, 2022. "Response Surface Methodology and Artificial Neural Networks-Based Yield Optimization of Biodiesel Sourced from Mixture of Palm and Cotton Seed Oil," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6130-:d:818287
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    References listed on IDEAS

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    1. Impha Yalagudige Dharmegowda & Lakshmidevamma Madarakallu Muniyappa & Parameshwara Siddalingaiah & Ajith Bintravalli Suresh & Manjunath Patel Gowdru Chandrashekarappa & Chander Prakash, 2022. "MgO Nano-Catalyzed Biodiesel Production from Waste Coconut Oil and Fish Oil Using Response Surface Methodology and Grasshopper Optimization," Sustainability, MDPI, vol. 14(18), pages 1-23, September.
    2. Ratna Dewi Kusumaningtyas & Normaliza Normaliza & Elva Dianis Novia Anisa & Haniif Prasetiawan & Dhoni Hartanto & Harumi Veny & Fazlena Hamzah & Miradatul Najwa Muhd Rodhi, 2022. "Synthesis of Biodiesel via Interesterification Reaction of Calophyllum inophyllum Seed Oil and Ethyl Acetate over Lipase Catalyst: Experimental and Surface Response Methodology Analysis," Energies, MDPI, vol. 15(20), pages 1-14, October.

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