Multiscale Modeling and Simulation of Polymer Blends in Injection Molding: A Review

Modeling and simulation of the morphology evolution of immiscible polymer blends during injection molding is crucial for predicting and tailoring the products’ performance. This paper reviews the state-of-the-art progress in the multiscale modeling and simulation of injection molding of polymer blends. Technological development of the injection molding simulation on a macroscale was surveyed in detail. The aspects of various models for morphology evolution on a mesoscale during injection molding were discussed. The current scale-bridging strategies between macroscopic mold-filling flow and mesoscopic morphology evolution, as well as the pros and cons of the solutions, were analyzed and compared. Finally, a comprehensive summary of the above models is presented, along with the outlook for future research in this field.

Effect of Variation of Injection Molding Parameters on Static, Dynamic and Thermo-Mechanical Material Properties of Filled Polymer Materials

A material (polymer + glass fibers) is characterized by its inhomogeneity and anisotropy. This material is subjected an injection molding simulation at first (generally unnewton type of fluid). Then the material is cooled and common structural analysis (static, dynamic and thermal) is performed. The cooled material has dissimilar mechanical properties for each of discrete element. Thus the mechanical properties (after simulation of load) will completely have different values when influence of injection molding is included.

Efficient Characterization and Modelling of Material Behaviour of LFT for Component Simulations

Modeling failure and progressive damage of long fibre reinforced thermoplastics (LFT) presents a challenging task since local inhomogeneities, anisotropic fibre orientations, and strain-rate dependence must be taken into account also on the microscale. We show that for simple geometries, the material behaviour of the composite can be modelled using layered geometrical models. But for more complex geometries, this approach fails since the fibre orientation distribution is inhomogeneous. In this case, multiscale methods allow the accurate and efficient prediction of the material behaviour with the local fibre orientation taken from an injection molding simulation. This material model can be extended to viscoplasticity and integrated into the NTFA-TSO method from Michel & Suquet (2016). In this way, we can obtain an accurate and efficient multiscale method for the realistic modelling of LFT.

An efficient coupled pressure–velocity solver for three-dimensional injection molding simulation using Schur complement preconditioned FGMRES

Purpose The purpose of this paper is to develop a coupled approach to solve the pressure–velocity-coupled problem efficiently in the three-dimensional injection molding simulation. Design/methodology/approach A fully coupled pressure–velocity algorithm is developed to solve the coupled problem, by treating the pressure gradient term implicitly. And, the Schur complement preconditioned FGMRES is applied to decompose the resulting coupled pressure–velocity equation into pressure and velocity subsystems. Then, BoomerAMG is adopted to solve the pressure subsystem, and block Jacobi preconditioned FGMRES is applied to the velocity subsystem. Findings According to the several experiments, the fully coupled pressure–velocity algorithm was demonstrated to have faster convergence than the traditional SIMPLE algorithm, and the calculating time was reduced by up to 70 per cent. And, the Schur complement preconditioned FGMRES worked more efficiently than block Gauss–Seidel preconditioned FGMRES, block-selective AMG and AMG with block ILU(0) smoother and could take at least 47.4 per cent less time. The proposed solver had good scalability for different-size problems, including various cases with different numbers of elements. It also kept good speedup and efficiency in parallel performance. Originality/value A coupled solver has been proposed to effectively solve the coupled problem in the three-dimensional injection molding simulation, which is more robust and efficient than existing methods.