Analysis and optimisation of transesterification parameters for high-yield Garcinia Gummi-Gutta biodiesel using RSM and TLBO

Abstract

ABSTRACT The consumption of fossil fuels is continuously increasing due to large number of automobiles and high demand for energy. Fossil fuels will not only become extinct in near future, but also pollute the environment. The present research work is focused on finding an eco-friendly alternate energy source through the production of bio-diesel. Naturally available low-cost Garcinia Gummi-Gutta seed was used to produce the biodiesel employing the transesterification process widely utilised in industries. The maximum biodiesel yield was primarily dependent on the optimisation of transesterification parameters (reaction time, percent of methanol and sodium hydroxide). Response Surface Methodologies (RSM) such as Box-Behnken design (BBD) and Central composite design (CCD) were used to conduct the experiments and analyse the transesterification parameters relationship with biodiesel yield. Results showed that, the methanol contribution was more as compared to sodium hydroxide and reaction time towards the yield of the biodiesel. The mathematical regression equations developed, related to biodiesel yield and transesterification parameters by utilising both the CCD and BBD models. The performance of BBD was found to be slightly better than that of CCD in making prediction of the biodiesel yield. Experimentally, the Teaching Learning-based Optimisation (TLBO) determined optimal transesterification parameters resulting to 96.2% biodiesel yield.