Production optimisation of mixed oil (rubber seed oil-fish oil) feedstock using response surface methodology and artificial neural network

This study is aimed at optimising the reaction parameters involved in transesterification of Mixed Non-edible Oil (rubber seed oil-fish oil) feedstock using response surface methodology (RSM) and artificial neural network (ANN). The reaction parameters such as the methanol-to-oil molar ratio (M:O),...

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Bibliographic Details
Published in:International journal of ambient energy 2023-12, Vol.44 (1), p.2336-2346
Main Authors: Srikanth, H. V., Praveena, B. A., Arunkumar, G. L., Balaji, S., Santhosh, N., Sridhar, K., Bharath Kumar, S.
Format: Article
Language:English
Subjects:
artificial neural network (ANN)
Box-Behnken design (BBD)
fish oil
optimisation
Rubber seed oil
transesterification
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Summary:This study is aimed at optimising the reaction parameters involved in transesterification of Mixed Non-edible Oil (rubber seed oil-fish oil) feedstock using response surface methodology (RSM) and artificial neural network (ANN). The reaction parameters such as the methanol-to-oil molar ratio (M:O), catalyst concentration (CC), reaction temperature (Rt) and the reaction time (RT) were investigated on biodiesel samples. The reaction process was optimised with a M:O of 7.5:1; a CC of 1.25 wt. %; Rt of 57.5°C and RT of 75 min with an optimum volumetric yield of 91.5 v/v%. The model attained from the results of analysis of variance indicates that the model developed was significant. A very small value of p (
ISSN:0143-0750
2162-8246
DOI:10.1080/01430750.2023.2236107