Simulação da produção de biodiesel usando o software COCO

Abstract

Currently, more than half of the global energy matrix comes from non-renewable sources, driving interest in biofuels. The main advantage of using biodiesel is the reduction of greenhouse gases. This study aimed to simulate biodiesel production using the COCO software. The use of computational tools, such as COCO, optimizes calculations that were previously performed manually, facilitating planning in the chemical industry. Thus, the simulation allows the optimization of reaction variables, and because it is free, the COCO software is a viable alternative within the chemical industry. The methodology was based on data collection from academic sources and renowned websites such as NIST (National Institute of Standards and Technology) and PubChem. Subsequently, spreadsheets were created with all the properties and components not included in the software's database. Finally, the thermophysical information was inserted into the ChemSep3 package, and the simulation was performed. The thermophysical properties of the oil components (triolein, diolein, and monoolein) were calculated using COCO software and compared to experimental data. Good agreement was observed, especially for monoolein, validating the simulated calculations. The boiling temperature, critical temperature, and critical volume showed proximity to the experimental values for macaúba oil. The simulation of the CSTR reactor revealed that, for a 60% conversion, a volume of 0.5 m³ (500 L) is sufficient under specific conditions (T = 333.15 K and P = 400 kPa). The volume versus conversion graph showed that additional increases in volume become ineffective due to kinetic equilibrium. Moreover, the concentration versus space-time analysis demonstrated rapid consumption of triglycerides and methanol, with gradual biodiesel formation until stability was reached at 20 minutes. Therefore, the simulation presented results consistent with the literature, validating the efficiency of the COCO software as a tool for modeling and optimization in biodiesel production.