Maximizing biodiesel production: An intelligent software-driven optimization of ultrasonic reactor operating variables

Abstract

The numerous advantages of integrating biodiesel with diesel engines have spurred many studies towards optimizing the production process's operating parameters. Ultrasonic reactors are renowned instruments for generating biodiesel from raw oil. This current research has varied the ultrasonic reactor's operating parameters to achieve maximum yield, aided by artificially intelligent software. The reactants employed to generate biodiesel were Eucalyptus oil combined with ethanol and sulphuric acid. The prime input factors considered were chemical reaction duration, molar ratio, frequency, energy requirement, and temperature. These parameters were varied and optimized to achieve maximum biodiesel yield, utilizing the best operating conditions for ultrasonic reactor as provided by the adaptive neuro-fuzzy inference system (ANFIS) and response surface methodology (RSM). The best reactor conditions for achieving a maximum yield of 96 % were 7.03 min, 29.05 kHz, 100 W, 33.48 °C, and 6.65 for chemical reaction duration, frequency, energy requirement, temperature, and molar ratio, respectively.