Integrated numerical simulation and quality attributes of soybean protein isolate extrusion under different screw speeds and combinations

Journal article

Sun, Dongyu, Zhou, Chengyi, Yu, Haoze, Wang, Bo, Li, Yang and Wu, Min. (2022). Integrated numerical simulation and quality attributes of soybean protein isolate extrusion under different screw speeds and combinations. Innovative Food Science and Emerging Technologies. 79, p. Article 103053. https://doi.org/10.1016/j.ifset.2022.103053

Publication dates
Authors	Sun, Dongyu, Zhou, Chengyi, Yu, Haoze, Wang, Bo, Li, Yang and Wu, Min
Abstract	A numerical simulation of the fluid-dynamic parameters (shear rate distribution, shear viscosity distribution and residence time) inside the barrel combined with extrudate properties, is a potential novel approach for investigating molten soybean protein isolate (SPI) under different screw speeds and combinations. Through finite element simulation, computer fluid dynamics and particle tracking simulation analysis, it was found that increasing the screw speed can increase the shear rate, decreased the shear viscosity of the SPI fluid, and reduced the RDT, thereby promoting the dispersion degree. The maximum shear rate and minimum shear viscosity were generated at the screw flight flanks, and the fluid underwent an alternate shearing force in the barrel. A small axial channel width can significantly promote the fluidity of molten proteins. In conclusion, SPI extrudates with a homogenous structure, smooth surface, and favourable colour and textual profile were produced at a relatively high screw speed (140 rpm).
Keywords	twin-screw extruder; numerical simulation; computer fluid dynamics (CFD); soybean protein isolate (SPI); residence time
Year	2022
Journal	Innovative Food Science and Emerging Technologies
Journal citation	79, p. Article 103053
Publisher	Elsevier Ltd
ISSN	1466-8564
Digital Object Identifier (DOI)	https://doi.org/10.1016/j.ifset.2022.103053
Scopus EID	2-s2.0-85132234740
Page range	1-22
Funder	National Natural Science Foundation of China (NSFC)
	Chinese Universities Scientific Fund
	Natural Science Foundation of Beijing Municipality
Publisher's version	License All rights reserved File Access Level Controlled
Output status	Published
Online	13 Jun 2022
Publication process dates
Accepted	06 Jun 2022
Deposited	10 Jan 2023
Grant ID	32171912
	2022TC079
	6182022

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