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In recent years, there has been an increasing demand for efficient mixers with high-quality mixing capabilities in the rubber product industry, with the focus of producing fuel-efficient tires. Depending on the functional characteristics of the tire and thus the compounding ingredients, different types of mixers can be used for the rubber mixing process. Hence, the choice of an appropriate mixer is critical in achieving the proper distribution and dispersion of fillers in rubber and a consistent product quality, as well as the attainment of high productivity. With the availability of high-performance computing resources and high-fidelity computational fluid dynamics tools over the last two decades, understanding the flow phenomena associated with complex rotor geometries such as the two- and four-wing rotors has become feasible. The objective of this article is to compare and investigate the flow and mixing dynamics of rubber compounds in partially filled mixing chambers stirred with three types of rotors: the two-wing, four-wing A, and four-wing B rotors. As part of this effort, all the 3D simulations are carried out with a 75% fill factor and a rotor speed of 20 rpm using a computational fluid dynamics (CFD) code. Mass flow patterns, velocity vectors, particle trajectories, and other mixing statistics, such as cluster distribution index and length of stretch, are presented here. All the results showed consistently that the four-wing A rotor was superior in terms of dispersive and distributive mixing characteristics compared with the other rotors. The results also helped to understand the mixing process and material movement, thereby generating information that could potentially improve productivity and efficiency in the tire manufacturing process.
In recent years, there has been an increasing demand for efficient mixers with high-quality mixing capabilities in the rubber product industry, with the focus of producing fuel-efficient tires. Depending on the functional characteristics of the tire and thus the compounding ingredients, different types of mixers can be used for the rubber mixing process. Hence, the choice of an appropriate mixer is critical in achieving the proper distribution and dispersion of fillers in rubber and a consistent product quality, as well as the attainment of high productivity. With the availability of high-performance computing resources and high-fidelity computational fluid dynamics tools over the last two decades, understanding the flow phenomena associated with complex rotor geometries such as the two- and four-wing rotors has become feasible. The objective of this article is to compare and investigate the flow and mixing dynamics of rubber compounds in partially filled mixing chambers stirred with three types of rotors: the two-wing, four-wing A, and four-wing B rotors. As part of this effort, all the 3D simulations are carried out with a 75% fill factor and a rotor speed of 20 rpm using a computational fluid dynamics (CFD) code. Mass flow patterns, velocity vectors, particle trajectories, and other mixing statistics, such as cluster distribution index and length of stretch, are presented here. All the results showed consistently that the four-wing A rotor was superior in terms of dispersive and distributive mixing characteristics compared with the other rotors. The results also helped to understand the mixing process and material movement, thereby generating information that could potentially improve productivity and efficiency in the tire manufacturing process.
Among several operational parameters such as rotor speed, fill factor and ram pressure, the orientation of the mixing rotors with respect to each other plays a significant role in the mixing performance. An understanding of the flow field and mixing characteristics associated with the orientations of the rotors will help in obtaining a final product with a better quality. For that purpose three phase angle orientations: 45°, 90° and 180° are investigated here in a 75% filled chamber with two rotors counter-rotating at an even speed of 20 min–1. Two dimensional, transient, isothermal, incompressible simulations are carried out using a CFD code. While an Eulerian multiphase method was used to solve for the transport variables in the two phases: rubber and air, the volume of fluid (VOF) method was used to solve for the interface between the two phases. A non-Newtonian Carreau-Yasuda model was used to characterize rubber. Massless particles were injected in the domain to calculate statistical quantities in order to assess dispersive and distributive mixing characteristics associated with rotor orientations. The flow field is analyzed via pressure and velocity contours. Dispersive mixing was analyzed through histograms of mixing index and cumulative probability distribution functions of maximum shear stress experienced by the particles. Distributive mixing was quantified statistically using cluster distribution index and interchamber material transfer. The phase angle of 180° was found to perform the best in terms of both dispersive and distributive mixing characteristics.
Three-dimensional, transient, isothermal, and incompressible computational fluid dynamics (CFD) simulations are carried out for rubber mixing with two counter-rotating rotors in a partially filled chamber in order to assess the effect of different speed ratios. The three different speed ratios that are investigated include 1.0, 1.125, and 1.5. In addition to the solution of the incompressible continuity and momentum equations, a Eulerian multiphase model is employed to simulate two phases, rubber and air, and the volume of fluid (VOF) technique is used to calculate the free surface flow between the phases. The Bird–Carreau model is used to characterize the non-Newtonian highly viscous rubber. Massless particles are injected in the simulations to obtain data required for statistical calculations related to dispersive and distributive mixing characteristics. Specifically, joint probability density functions of mixing index and shear rate, and cumulative distribution functions of maximum shear stress are calculated to assess dispersive mixing, while distributive mixing capabilities are evaluated using various quantities such as cluster distribution index, axial distribution, interchamber particle transfer, and segregation scale. Results showed the speed ratio 1.125 to be consistently superior to 1.5 and 1.0, in terms of both dispersive and distributive mixing performance. The large speed difference between the rotors in the case of 1.5 caused it to perform the worst.
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