Three-dimensional smoothed particle hydrodynamics simulation for injection molding flow of short fiber-reinforced polymer composites

He, Liping; Lu, Gang; Chen, Dachuan; Li, Wenjun; Lu, Chunsheng

doi:10.1088/1361-651x/aa6dc9

Cited by 21 publications

(9 citation statements)

References 40 publications

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“…Yashiro et al [33,34] connected particles to rigid bodies for modeling the injection molding of dilute short-fiber-reinforced composites using a moving particle semi-implicit method. Recently, a very similar approach using SPH was reported by He et al [35,36]. However, both showed only short time periods when comparing the simulation to Jeffery's equation and did not investigate the interaction between fibers.…”

Section: Resolved Methodsmentioning

confidence: 93%

Parameter Identification of Fiber Orientation Models Based on Direct Fiber Simulation with Smoothed Particle Hydrodynamics

et al. 2020

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The behavior of fiber suspensions during flow is of fundamental importance to the process simulation of discontinuous fiber reinforced plastics. However, the direct simulation of flexible fibers and fluid poses a challenging two-way coupled fluid-structure interaction problem. Smoothed Particle Hydrodynamics (SPH) offers a natural way to treat such interactions. Hence, this work utilizes SPH and a bead chain model to compute a shear flow of fiber suspensions. The introduction of a novel viscous surface traction term is key to achieve full agreement with Jeffery’s equation. Careful modelling of contact interactions between fibers is introduced to model suspensions in the non-dilute regime. Finally, parameters of the Reduced-Strain Closure (RSC) orientation model are identified using ensemble averages of multiple SPH simulations implemented in PySPH and show good agreement with literature data.

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Section: Resolved Methodsmentioning

confidence: 93%

Parameter Identification of Fiber Orientation Models Based on Direct Fiber Simulation with Smoothed Particle Hydrodynamics

et al. 2020

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“…for every bead in the fiber. The uniqueness of this model is that it is capable of simulating the curvature of the fibers at the fiber–fiber crossovers without allowing the fibers to penetrate into one another, which is a major advantage over the previous fiber‐mat generation methods …”

Section: Numerical Simulationsmentioning

confidence: 99%

Empirical model to simulate morphology of electrospun polycaprolactone mats

Yousefi

Tang

Tafreshi

et al. 2019

J of Applied Polymer Sci

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This work is the first to report a study aimed at generating 3D virtual geometries that represent the microstructure of an electrospun fibrous mat comprised curly fibers. Polycaprolactone (PCL) mats are considered in our study as an example of such fibrous structures. We started with simulating the formation of PCL filaments and observed good agreement between the predicted and measured fiber diameters. In the absence of quantitative information about the shape of a curly PCL fiber, we treated these fibers as arrays of beads arranged on epitrochoid profiles. We then used the fiber deposition diameter and velocity in a mass-spring-damper (MSD) model to generate 3D fibrous geometries comprised hundreds of such curly fibers. The damping and spring constants in the MSD model were obtained through calibration with experimental data reported for single electrospun PCL nanofibers. The size of the epitrochoid-like fibers was obtained empirically through matching the average thickness of the resulting mats with those measured experimentally. With the calibrated code, we studied the effects of electrospinning conditions on the porosity of PCL nanofiber mats. It was found that increasing the voltage or decreasing the needle-to-collector distance results in PCL mats with thicker fibers, and consequently, lower porosities.

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“…Xu and Yu [38] used a modified SPH algorithm to simulate the nonisothermal filling flow in annular, F-shaped, and N-shaped cavities. He et al [39] modeled short fibers as rigid short rods and used the SPH method to simulate the 3D injection molding filling flow and fiber distribution of short fiber reinforced polymer composites. Wu et al [40] simulated the injection molding of short fiber composites coupling the SPH and discrete element method (DEM), where the fibers are with deformation and fracture.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Polymer Melt Injection Molding Filling Flow Based on an Improved SPH Method with Modified Low‐Dissipation Riemann Solver

Ren

et al. 2021

Macro Theory & Simulations

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Simulations are performed for the polymer melt injection molding filling flow using an improved SPH (smoothed particle hydrodynamics) method. For improving the numerical stability of the high-pressure and high-viscosity injection molding filling simulation, a modified low-dissipation Riemann solver is proposed, and the Tait equation of state and several improvements are adopted in the improved SPH method. Simulations with three cavities are performed for verification of the SPH method, including a simple long rectangular cavity and two relatively complex cavities for study of injection flow balancing. For each cavity, the pressure and velocity results of the injection molding filling simulation are demonstrated, discussed, and compared with the results of the corresponding Moldflow simulation. Furthermore, results of particle motion tracking are also analyzed for an insight into the fountain flow effect. The SPH simulation results indicate that the improved SPH method can well weaken the non-physical pressure oscillation with reasonable pressure results and controlled melt compressibility, and the SPH results are in good agreement with the Moldflow results.

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Three-dimensional smoothed particle hydrodynamics simulation for injection molding flow of short fiber-reinforced polymer composites

Cited by 21 publications

References 40 publications

Parameter Identification of Fiber Orientation Models Based on Direct Fiber Simulation with Smoothed Particle Hydrodynamics

Parameter Identification of Fiber Orientation Models Based on Direct Fiber Simulation with Smoothed Particle Hydrodynamics

Empirical model to simulate morphology of electrospun polycaprolactone mats

Simulation of Polymer Melt Injection Molding Filling Flow Based on an Improved SPH Method with Modified Low‐Dissipation Riemann Solver

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