Performance comparison of empirical model and Particle Swarm Optimization &amp; its boiling point prediction models for waste sunflower oil biodiesel

Olusegun D. Samuel; Mohammad Kaveh; Oluwayomi J. Oyejide; P.V. Elumalai; Tikendra Nath Verma; Kottakkaran Sooppy Nisar; C Ahamed Saleel; Asif Afzal; O.S.I. Fayomi; H.I. Owamah; Selçuk Sarıkoç; Christopher C. Enweremadu

Case Studies in Thermal Engineering (May 2022)

Performance comparison of empirical model and Particle Swarm Optimization & its boiling point prediction models for waste sunflower oil biodiesel

Olusegun D. Samuel,
Mohammad Kaveh,
Oluwayomi J. Oyejide,
P.V. Elumalai,
Tikendra Nath Verma,
Kottakkaran Sooppy Nisar,
C Ahamed Saleel,
Asif Afzal,
O.S.I. Fayomi,
H.I. Owamah,
Selçuk Sarıkoç,
Christopher C. Enweremadu

Affiliations

Olusegun D. Samuel: Department of Mechanical Engineering, Federal University of Petroleum Resources, P.M.B 1221, Effurun, Delta State, Nigeria; Department of Mechanical Engineering, University of South Africa, Science Campus, Private Bag X6, Florida, 1709, South Africa; Corresponding author. Department of Mechanical Engineering, Federal University of Petroleum Resources, P.M.B 1221, Effurun, Delta State, Nigeria.
Mohammad Kaveh: Department of Petroleum Engineering, College of Engineering, Knowledge University, 44001, Erbil, Iraq
Oluwayomi J. Oyejide: Department of Mechanical Engineering, Federal University of Petroleum Resources, P.M.B 1221, Effurun, Delta State, Nigeria
P.V. Elumalai: Department of Mechanical Engineering, Aditya Engineering College, Surampalem, India; Department of Mechanical Engineering, Jawaharlal Nehru Technology University Kakinada, Kakinada, East Godavari District, Andhra Pradesh, India
Tikendra Nath Verma: Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, MP, 462003, India
Kottakkaran Sooppy Nisar: Department of Mathematics, College of Arts and Sciences, Wadi Aldawaser, 11991, Prince Sattam bin Abdulaziz University, Saudi Arabia; Corresponding author. Department of Mathematics, College of Arts and Sciences, Wadi Aldawaser, 11991, Prince Sattam bin Abdulaziz University, Saudi Arabia.
C Ahamed Saleel: Department of Mechanical Engineering, College of Engineering, King Khalid University, PO Box 394, Abha, 61421, Saudi Arabia
Asif Afzal: Department of Mechanical Engineering, P. A. College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi), Mangalore, 574153, India; University Centre for Research & Development, Department of Computer Science and Engineering, Chandigarh University, Gharuan, Mohali, Punjab, India; Department of Mechanical Engineering, School of Technology, Glocal University, Delhi-Yamunotri Marg, SH-57, Mirzapur Pole, Saharanpur District, Uttar Pradesh, 247121, India; Corresponding author. Department of Mechanical Engineering, P. A. College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi), Mangalore, 574153, India.
O.S.I. Fayomi: Department of Chemical, Metallurgical and Materials Engineering, Tshwane University of Technology, P.M.B. X680, Pretoria, South Africa; Department of Mechanical and Biomedical Engineering, Bells University of Technology, Ota, Nigeria
H.I. Owamah: Department of Civil and Environmental Engineering, Delta State University, Oleh Campus, Abraka, Delta State, Nigeria
Selçuk Sarıkoç: Department of Motor Vehicles and Transportation Technologies, Amasya University, Tasova Yuksel Akin Vocational School, Amasya, Turkey
Christopher C. Enweremadu: Department of Mechanical Engineering, University of South Africa, Science Campus, Private Bag X6, Florida, 1709, South Africa

Journal volume & issue: Vol. 33
p. 101947

Abstract

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The absence of correlations for predicting the boiling point of biodiesels prevents fuel users to achieve effective engine performance. Among the quality regulator of rudimentary fuel properties is the boiling point and its absence in literature is preventing fuel handlers to achieve actual engine performance. In this study, the mechanism of sunflower oil methanolysis was investigated by Response Surface Methodology (RSM) and Particle Swarm Optimization (PSO). The empirical model (EM) was utilized to correlate the optimal yield and trans-esterification variables for methylic biodiesel production. Thereafter, statistical regression techniques were employed to model the MBP of biodiesel vs. biodiesel fraction and MBP of biodiesel vs. kinematic viscosity. The yield of waste sunflower oil methyl ester (WSOME) (97%) was the uppermost at the methanol/SFO molar ratio of optimal of 6/1, KOH of 1 %wt, and retention time of 78 min. The PSO model exhibited an advanced coefficient of determination, and an inferior value of root mean squared errors related to the RSM model. PSO predicted values, as related to RSM predicted yield shows its dependability and expediency for prediction deprived of conservative experimentation. The fuel properties of the WSOME synthesized were within the ranges of established green fuel standards. The RSM with PSO has been exhibited efficient tools for exploring the methylic biodiesel production from WSO. Least square regression and parabolic equation correlated MBP as a function of bio-diesel fraction and MBP as a function of kinematic viscosity. In conclusion, the results of this study can be useful for biodiesel production from industrial waste oil and the prediction of MBP in the biodiesel industry.

Published in Case Studies in Thermal Engineering

ISSN: 2214-157X (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Technology: Engineering (General). Civil engineering (General)
Website: http://www.journals.elsevier.com/case-studies-in-thermal-engineering/

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