Dataset on optimized biodiesel production from seeds of Vitis vinifera using ANN, RSM and ANFIS

V Hariram; A Bose; S Seralathan

doi:10.1016/j.dib.2019.104298

Dataset on optimized biodiesel production from seeds of Vitis vinifera using ANN, RSM and ANFIS

Data Brief. 2019 Jul 23:25:104298. doi: 10.1016/j.dib.2019.104298. eCollection 2019 Aug.

Authors

V Hariram¹, A Bose¹, S Seralathan¹

Affiliation

¹ School of Mechanical Sciences, Hindustan Institute of Technology and Science, Chennai, Tamilnadu, India.

Abstract

This dataset disclose the investigational data on the extraction of bio-oil from seeds of Vitis vinifera through combination of mechanical pressing and soxhlet solvent extractor. Biodiesel is produced through single stage base catalysed transesterification process due to lower free fatty acid content in the Vitis vinifera bio-oil. Independent variable process parameters like molar ratio, reaction time and catalyst concentration are optimized using Artificial Neural Network, Response Surface Methodology and Adaptive Neuro-Fuzzy Interference System to predict the maximum biodiesel yield and the results are compared with the experimental data. Response Surface Methodology predicted a maximum Vitis vinifera biodiesel yield of 97.62% at methanol to oil molar ratio 0.2758 v/v, catalyst concentration 1.045 gm of NaOH and reaction duration of 1.11 hrs which is also confirmed with experimental results.

Keywords: ANFIS; ANN; Molar ratio; RSM; Transesterification; Vitis vinifera biodiesel.