Horn ultrasonic‐assisted pregelatinized starch with various streamline patterns as a green process: Computational fluid dynamics and microbubble formation of process

Abstract

AbstractThe ultrasound‐assisted pregelatinization starch (UAPS) is considered as a physical method for starch modification. In this study, the effect of ultrasonic control parameters, including power, probe size, temperature, and time was investigated in order to predict microbubble formation and cavitation process as a two dimensional axisymmetric computational fluid dynamics (CFD) model to optimize the UAPS process. The cavitation phenomenon and the bubble dynamics were further investigated with regards to the mentioned parameters. Results showed that with the increase in probe diameter from 20 mm to 100 mm, a new pattern of streamlines were generated at the bottom of the container, increasing the turbulence among bubbles. This is mainly due to collapsing bubbles, resulting in a huge amount of energy released which accelerates heat and mass transfer to the fluid. According to the results obtained from the dynamics of bubbles, the maximum radius of the bubbles had a rising pattern with the increase in the probe size (from 20 to 100 mm), amplitude (from 25 to 45%) and temperature (from 35 to 65°C); moreover, the energy of the bubble slightly increased with the increase in liquid temperature and probe size.Practical applicationsThe physical modifications of starch structure are more widely employed since it is safer and without impurities, which have strong effects on different component functionalities. Pregelatinization is one of the most popular industrial methods of physically modifying starch. Pregelatinized. The ultrasound‐assisted pregelatinized starch as physical modification offers many advantages, mainly the declined utilize of chemicals and processing time, serving as an environment‐friendly processing technology, high selectivity method. Use of computational fluid dynamics is a suitable approach to assessing the data pertaining to the physical features of the ultrasonication process. We underscored the importance of filling the gaps of knowledge concerning modeling sonication process to produce the efficient ultrasound‐assisted pregelatinized starch under various ultrasound power, probe size and fluid temperature to predict microbubble formation, heat and energy transfer.