Experimental and CFD simulation studies of biodiesel production in an in-house Tesla-shaped microreactor

Abstract

Continuous flow microreactors have been shown to be effective for biodiesel production, and the Tesla-shaped microreactor, in particular, is one of the proposed microreactors for this application. However, its applicability in the industry is still limited. Therefore, comprehensive simulation studies that agree with the real processes need to be performed to allow a deep understanding of the process. A 2D CFD simulation model is constructed in COMSOL Multiphysics software to study the performance of a Tesla-shaped microreactor fabricated in-house- for biodiesel production from waste cooking oil (WCO). The model is thoroughly analyzed and validated experimentally at different operating conditions. The percentage yield values resulting from the simulation were found to be 84.13% at a temperature of 50 °C, 90.79% at a temperature of 55 °C, and 94.85% at a temperature of 60 °C, which deviated from the experimental values by 2.73%, 1.15%, and 1.98%, respectively. On the other hand, an alcohol-to-oil molar ratio of 12:1 resulted in a simulation percentage yield of 94.85% which deviates from the experimental values by 1.98%, while at a molar ratio of 9:1, the simulation yielded 93.67% with a deviation of 3.33% from the experimental results. At a lower ratio of 6:1, the simulation percentage yield was found to be 69.89%, and it deviated by 18.82% from the experimental results. This study presents a novel combination of simulation and experimental validation for the Tesla-shaped microreactor in biodiesel production from waste cooking oil., which is a topic with limited existing research although it significantly contributes to understanding the process at different operating conditions. The high agreement between simulation and experimental results demonstrates the accuracy and suitability of the simulation for studying the% conversion, and potential investigation such as the molar flow rate variations, and reaction rates under different conditions. This approach offers a cost-effective and efficient solution for optimizing biodiesel production, reducing the need for extensive experimental trials, and saving significant time and effort.