Digital twin of waste cooking oil biodiesel: optimizing n-Butanol blends via mixture-process design

Abstract

Abstract

Although waste cooking oil (WCO)-based biodiesel represents a sustainable alternative within the context of the circular economy, its direct application remains constrained by drawbacks such as high density, high kinematic viscosity, and elevated surface tension. This study aims to improve the weak thermophysical properties of WCO biodiesel through the addition of n-butanol, while simultaneously tailoring its density and kinematic viscosity to fall within the EN 590 diesel standard limits. To this end, rather than relying on costly and time-consuming trial-and-error approaches, this research introduces an innovative methodology based on the integration of the DWSIM process simulator and Mixture-Process Design. The chemical structure of the WCO biodiesel was defined as a surrogate model in the DWSIM environment using the mass fractions of its primary Fatty Acid Methyl Ester (FAME) components (methyl oleate, methyl linoleate, methyl palmitate, and methyl stearate). The fundamental thermophysical properties of the model were then validated against reference experimental data. To statistically model the constrained mixture space, a 15-run experimental matrix was generated utilizing the D-Optimal Extreme Vertices algorithm. The developed regression models accounted for the variations in kinematic viscosity, density, and surface tension with high statistical accuracy (R2 > 96.5%, p < 0.05). In the final stage, Multiple Response Optimization was performed using Derringer's Desirability Function to reconcile the conflicting targets of density and viscosity into a unified metric. The analysis indicated a maximum desirability score (D = 0.835) for a blend comprising 72.8 wt.% WCO and 27.2 wt.% n-butanol (WCO72.8/NB27.2) at an operating temperature of 30 °C. At this global optimum point, the density and kinematic viscosity of the fuel were determined as 840.0 kg/m3 and 2.72 mm2/s, respectively. Overall, the findings suggest that n-butanol acts as a highly effective solvent in reducing the internal friction and surface tension of waste oil biodiesels characterized by heavy ester profiles. Furthermore, the results indicate that the DWSIM-RSM digital integration can be utilized with high reliability in alternative fuel blending optimizations.