ABSTRACT
Biodiesel production by ultrasonication was carried out from non- edible Kigelia africana oil using a novel heterogeneous base catalyst by the calcination of Pyrgostylus striatulus shells. A comparative study of expert optimization systems namely Response surface methodology (RSM) and Artificial neural intelligence (ANN) was executed on optimization of the process parameters for the transesterification process. The process parameters considered were alcohol to oil ratio (9:1 to 15:1 mol/mol), catalyst weight (3–5 wt.%) and ultrasonication time (30–60 min) on methanolysis process. Statistical error analysis was performed. Quadratic regression model with R2 value of 0.9854 and 0.9788 was observed for ANN and RSM, respectively. The results of the current work indicated ANN model was a cut above RSM. The physio-chemical properties of biodiesel produced were assessed and found to be within the standard ASTM limits indicating the bio-fuel to be suitable.
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Notes on contributors
Umaiyambika Neduvel Annal
Umaiyambika Neduvel Annal is working as an Assistant Professor in Saveetha Engineering college. She is currently pusuing her PhD degree in Chemical Engineering field and obtained her post graduate degree from Anna University. She has teaching and research experience of over 10 years. Her research interests are Biofuels and wastewater treatment analysis.
Arunodhaya Natarajan
Arunodhaya Natarajan is currently working as Assistant Professor in Agni College of Technology. He has obtained his Master’s degree from Anna University. He has teaching and research experience of more than ten years. His research interests are mainly in biodiesel production and hydrotropic extraction.
Renganathan Sahadevan
Renganatha Sahadevan is currently working as Professor in Anna University. He has teaching and research experience of more than twenty years. He has guided many PhD scholars. His research domain are biofuel production and nanoparticle synthesis.