Optimisation of CaO-Al2O3-SiO2-CaSO4-based catalysts performance for methanolysis of waste lard for biodiesel production using response surface methodology and meta-heuristic algorithms
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Date
2022-02
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FuelProcessingTechnology: ElsevierB.V.
Abstract
The CaO-Al2O3-SiO2-CaSO4-based solid catalysts developed from calcium carbide residue (CCR) was investigated
for biodiesel production using waste lard in optimisation and regeneration studies. The catalysts were synthe
sized by calcination of the CCR at the temperature of 500, 700 and 900 ◦C and sulphonation, to give Cat500,
Cat700 and Cat900 respectively. The catalysts were studied to optimise the biodiesel yield from waste lard using
combinations of response surface methodology (RSM) and meta-heuristic algorithms such as particle swarm
optimisation (PSO), genetic algorithm (GA) and firefly algorithm (FA). The process parameters investigated were
methanol: oil molar ratio (6–12 w/w), reaction temperature (50–60 ◦C), reaction time (1–4 h), catalyst quantity
(5–15 % (w/w)) and catalyst type (Cat500, Cat700 and Cat900). The study revealed that the 12:1 MeOH: oil molar
ratio, 59.97 ◦C reaction temperature, 1 h reaction time, 5% (w/w) catalyst quantity and Cat500 catalyst type
gave biodiesel yield of 96.35%. The performance of the meta-heuristic algorithms based on the optimisation
output compared well with that of the RSM. This study concludes that the catalyst developed from the CCR can
be regenerated after the ninth cycle of usage and re-utilised for efficient biodiesel production.
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Transesterification Vegetable oil Animal fat Genetic algorithm Particle swarm optimisation Firefly algorithm Fatty acid methyl esters