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MATHEMATICAL MODELLING OF QUANTIFYING BIOETHANOL FUEL PRODUCTION FROM PINEAPPLE WASTE

  • Monzur Imteaz - Department of Civil and Construction Engineering, Swinburne University of Technology, Australia
  • ABM Hossain - Department of Biology, Imam Muhammad Ibn Saud Islamic University, Saudi Arabia
  • Amimul Ahsan - Department of Civil and Environmental Engineering, Islamic University of Technology, Bangladesh
  • Parminder Kaur - Circular Economy Solutions, Geological Survey of Finland, Finland

DOI 10.31025/2611-4135/2024.18356

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Copyright: © 2023 CISA Publisher

Abstract

Lack of confidence in potential bioenergy production and net benefit hinders rapid implementations of such sustainable energy productions from different waste sources. With the aim of accelerating real-life implementations of more bioenergy productions, this paper presents development of a simple mathematical model, which can be used to evaluate potential bioethanol production capacity from pineapple waste under different input conditions. Based on an earlier experimental study, the mathematical model was developed depending on three contributing factors; pH, temperature and substrate concentration as considered in the earlier experimental study. Results from the developed mathematical formulation were compared with the experimental data from the earlier original study. It is found that the developed model is quite capable to estimate potential bioethanol productions from pineapple waste. Model estimated results are having a coefficient of correlation of 0.84 with the measured data. Standard errors of the model’s estimations are also quite low; RMSE = 0.49, MAE = 0.39 and RAE = 0.06. To facilitate a wider industrial generation, a basic mathematical model framework for economic analysis is proposed involving evaluation of net present values of expected future yields, as well as costs (initial and maintenance). Such mathematical model of economic analysis will help stakeholders on selecting optimum input parameters in achieving targeted benefit through optimised energy consumption.

Keywords

Editorial History

  • Received: 27 Sep 2023
  • Revised: 23 Jan 2024
  • Accepted: 26 Feb 2024
  • Available online: 20 Mar 2024

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