Reliability on the observed results of biodiesel prepared from high viscous rubber seed oil (RSO) using fluorite and calcined limestone as catalysts has been studied using uncertainty error analysis. In this study, the error analysis was performed for three different deviations 5, 10, and 15% of optimum process parameter conditions of 12:1 methanol: oil molar ratio (mol/mol), 4 (wt %) of catalyst concentration, and 5(h) of reaction time, respectively. All the uncertainty experiments were performed for upper level and lower level of every deviation mentioned with. From these experiments, it was observed that methanol: oil molar ratio (mol/mol) shows more error on a small deviation of optimum conditions when compared with catalyst concentration and reaction time, respectively. It is also observed that molar ratio is the most sensitive process parameter in biodiesel preparation from RSO using fluorite and calcined limestone as heterogeneous base catalysts when compared to catalyst concentration and reaction time, respectively.
In the present study, acid value optimization in continuous biodiesel production from high viscous nonedible rubber seed oil (RSO) is presented. Gradual reduction in acid value from 67.6 (mg KOH/g oil) (raw RSO) to 3.55 (mg KOH/g oil) (pretreated RSO) to 0.25 (mg KOH/g oil) (synthesized biodiesel) is detected at reaction conditions of 9:1 alcohol:feedstock (methanol:oil (molar ratio)) (mol/mol), 4 h of residence time, and 5 wt% (oil) of catalyst concentration. Optimization of experimental factors is studied using well‐known data‐based tools called response surface methodology (RSM) and artificial neural network (ANN), respectively. A significant second‐order quadratic model with alcohol:feedstock molar ratio (mol/mol) as most influencing experimental factor is observed from ANOVA analysis of RSM studies. A mean‐square error (MSE) of 0.001245 is observed with the best validation performance of 0.0014716 at epoch‐3 in ANN modeling. Comparing the coefficient of determination (R2) of value 0.8906 (from RSM studies) with the value of 0.99 (from ANN modeling) reveals that ANN is the best fit model with experimental value in acid value optimization of continuous biodiesel production from RSO.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.