Non-isothermal flow of polymers into two-dimensional, thin cavity molds: a numerical grid generation approach

Subbiah, Surej Kumar; Trafford, D.L.; Güçeri, Selçuk I.

doi:10.1016/0017-9310(89)90130-0

Cited by 52 publications

(20 citation statements)

References 17 publications

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“…The CVFEM method is implemented with an Euler implicit formulation to advance in time while central differences and an exponential interpolation scheme for the diffusive and convective terms, respectively. The implemented method is verified through reported experimental [18] and numerical data [3].…”

Section: Introductionmentioning

confidence: 86%

“…In order to validate the proposed scheme and the implemented numerical code, the experimental filling process studied by Subbiah et al [18] is replicated. In this experiment, corn syrup enters to a cavity (0.303m x 0.20 m) with a constant velocity (0.031 m/s) through an opening (0.02 m), in the upper left side.…”

Section: Validation: Injection Molding Of a Newtonian Fluid In A 2d Cmentioning

confidence: 99%

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Two-Dimensional Non Newtonian Fluid Injection Moulding Filling Improved With a Cvfem/Vof Method

Salinas¹,

Vasco²,

Moraga³

2014

Proceedings of 10th World Congress on Computational Mechanics

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Abstract. A new method based on volume of fluid (VOF) for interface tracking in the simulation of injection molding is presented. The proposed method is comprised by two main stages: accumulation and distribution of the volume fraction. In the first stage the equation for the volume fraction with a non-interfacial flux condition is solved meanwhile in the second stage the accumulated volume of fluid that arises as a consequence of the application of the first one is dispersed. This procedure guarantees that the fluid fills the available space without dispersion of the interface. The mathematical model is based on two-phase transport equations which are numerically integrated through the Control Volume Finite Element Method (CVFEM). The numerical results for

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Section: Introductionmentioning

confidence: 86%

Section: Validation: Injection Molding Of a Newtonian Fluid In A 2d Cmentioning

confidence: 99%

Two-Dimensional Non Newtonian Fluid Injection Moulding Filling Improved With a Cvfem/Vof Method

Salinas¹,

Vasco²,

Moraga³

2014

Proceedings of 10th World Congress on Computational Mechanics

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“…The initial neural network training data were obtained from a first-principles-based process model rather than from an actual manufacturing operation. The process model utilized in this study is called TGMOLD and has been developed by Gfi9eri and coworkers (Trafford, 1986;Subbiah et al, 1989). This software package simulates the filling stage of molding processes using Navier-Stoke's equations with a Hele-Shaw flow approximation.…”

Section: Application Of Neural-network-based Control To Injection Molmentioning

confidence: 99%

A comparative study of nonlinear optimization and Taguchi methods applied to the intelligent control of manufacturing processes

Coulter

1996

J Intell Manuf

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The current investigation focused on neural-network-based control of manufacturing processes utilizing an optimization scheme. In an earlier study, Demirci and Coulter introduced the utilization of neural networks for the intelligent control of molding processes. In that study, a forward model neural network, employed with a search strategy based on the factorial design of experiments method, was shown to successfully control the flow progression during injection molding processes. Recently, Demirci et al. showed that the search mechanism based on the factorial design of experiments method can be intolerable in time during on-line control of manufacturing processes, and suggested an inverse model neural network. This inverse model neural network was shown to be beneficial as it totally eliminated time-consuming parameter searches, but it required a harder mapping than the forward model neural network and thus its performance was inferior. In the present study, the authors investigated two different optimization methods that were utilized in making the search method of the forward control scheme more efficient. The first method was Taguchi's method of parameter design, and the second method was a nonlinear optimization method known as Nelder and Mead's downhill simplex method. These two methods were separately utilized in creating an efficient search method to be used with the forward model neural network. The performance of the resulting two control methods was compared with each other as well as with that of the forward control scheme utilizing a search strategy based on the factorial design of experiments method. Although the applications in this study were on molding processes, the method can be applied to any manufacturing process for which a process model and an in-situ sensing scheme exists. 4-

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“…The results were satisfactory in predicting weld-line formation and the pressure history at specific locations in the mold. Trafford et al [32] and Subbiah et al [33] applied a numerical grid generation technique to simulate the non-isothermal injection mold filling of complex planar shapes. The temperature calculations are performed using a transient three-dimensional energy equation.…”

Section: Studies On Flow Kinematicsmentioning

confidence: 99%

“…X-ray diffraction technique is used by Malik and Prud'homme [54] and Monge et al [55] to determine the orientation of mica flakes in composites. Malik [30,33].…”

Section: Studies On Fiber Reinforcementmentioning

confidence: 99%

A Review of Fiber-Reinforced Injection Molding: Flow Kinematics and Particle Orientation

Altan

1990

Journal of Thermoplastic Composite Materials

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The existing flow and particle orientation models applicable to fiberreinforced injection molding are reviewed. After a brief description of injection molding, previous studies on the flow kinematics and fiber reinforcement are presented. Basics of Hele-Shaw flows are described Including the commonly used viscosity models and fountain flow effects. Some of the existing models for particle orientation are analyzed with particular emphasis on the amsotropic description of the material system. Concentration regions for short fiber suspensions are defined and relevant constitutive equations are discussed. A few example solutions are also given which describe the three-dimensional orientation field for the filling of a sudden expansion cavity, depicting skin-core orientation structure.

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Non-isothermal flow of polymers into two-dimensional, thin cavity molds: a numerical grid generation approach

Cited by 52 publications

References 17 publications

Two-Dimensional Non Newtonian Fluid Injection Moulding Filling Improved With a Cvfem/Vof Method

Two-Dimensional Non Newtonian Fluid Injection Moulding Filling Improved With a Cvfem/Vof Method

A comparative study of nonlinear optimization and Taguchi methods applied to the intelligent control of manufacturing processes

A Review of Fiber-Reinforced Injection Molding: Flow Kinematics and Particle Orientation

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