2020
DOI: 10.1002/ep.13564
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Identification of sensitive process parameter of rubber seed oil conversion to biodiesel using fluorite and calcined limestone as catalysts—Uncertainty error analysis

Abstract: 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 le… Show more

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Cited by 6 publications
(3 citation statements)
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“…Reduced yield at higher oil/methanol ratios occurs as a result of dissolved glycerol in the excess methanol inhibiting the reaction, leading to a negative equilibrium shift 41. This result conforms to previous observations by Bharadwaj et al 42 who, through uncertainty analysis, observed that for two different catalysts, the methanol/oil molar ratio was the most sensitive parameter for the conversion of rubber seed oil to biodiesel. They further noted a significant drop in conversion at molar ratios lower than the optimum values, which agrees with our observation.…”
Section: Resultssupporting
confidence: 90%
“…Reduced yield at higher oil/methanol ratios occurs as a result of dissolved glycerol in the excess methanol inhibiting the reaction, leading to a negative equilibrium shift 41. This result conforms to previous observations by Bharadwaj et al 42 who, through uncertainty analysis, observed that for two different catalysts, the methanol/oil molar ratio was the most sensitive parameter for the conversion of rubber seed oil to biodiesel. They further noted a significant drop in conversion at molar ratios lower than the optimum values, which agrees with our observation.…”
Section: Resultssupporting
confidence: 90%
“…Uncertainty error analysis is related to the deviation of experimental output responses and can be resolved effectively. 41 The results have been given with uncertainty values in Table 7.…”
Section: Resultsmentioning
confidence: 99%
“…When developing a SA, it is critical to understand the relationships between the unknown input parameters. 47 The goal of employing RSM as a sensitivity analysis method is to increase the analyst's awareness of the sensitivity between the model's output (response) and its related input parameters and then utilize this information to enhance the decision model. Multi-objective optimization Box-Behnken response surface methodology…”
Section: Discussionmentioning
confidence: 99%