Extension of SPH to simulate non-isothermal free surface flows during the injection molding process

This article presents an extension of smoothed particle hydrodynamics (SPH) to non-isothermal free surface flows during the injection molding process. Specifically, we use the method presented by Xu and Yu, Appl. Math. Model. 48 (2017) pp. 384–409, in which the corrected kernel gradient is implemented to increase the computational accuracy and the Rusanov flux is introduced into the continuity equation to alleviate large and random pressure oscillations. To model non-isothermal free surface flows, a working SPH discretization of the temperature equation is derived. An enhanced treatment of the wall boundary is further developed, which can model arbitrary-shaped mold walls. The proposed SPH method is first validated by solving non-isothermal Couette flow and non-isothermal injection molding of a circular disc with a core and comparing the SPH results with those obtained by other numerical methods or experiments. We then extend the numerical method to non-isothermal injection molding of F-shaped and N-shaped cavities. The convergence of the method is examined with several different particle sizes. The effects of the operating conditions (e.g., injection temperature, temperature of the mold wall, and injection velocity) on the flow behavior are analyzed. All the results illustrate that the present SPH method is a powerful computational tool for simulations of non-isothermal free surface flows during the injection molding process.     

Numerical simulation of gas-assisted injection molding using CLSVOF method

It is a typical gas-liquid two phase flow phenomenon that gas penetrates the polymer melt in gas-assisted injection molding (GAIM) process. Numerical simulation is now playing an important role in GAIM, in which the accurate simulation of moving interface is of great importance. The level set (LS) method is a popular interface tracking method, but it does not ensure naturally mass-conservation. In order to improve the mass-conservation of LS method, a coupled level-set and volume-of-fluid (CLSVOF) method with mass-correction is presented for the numerical simulations of interfacial flows in GAIM. The performance of this CLSVOF method is demonstrated by two numerical tests including the three-dimensional deformation field test and the dam break problems. Finally the CLSVOF method is employed to simulate the 3D moving interfaces in GAIM, including gas-melt interface and the melt-front interface. The influences of melt temperature and gas delay time are also analyzed detailedly. As a case study, the processes that gas penetrates the polymer melt in complex cavities are also simulated using this method, and the simulation results are in agreement with those obtained by other researchers.     

Simulating of a pressing process of a viscoelastic polymer melt

A well known and often used method to obtain anisotropic polymer films is the so-called pressing process. Here, films are squeezed under high temperatures, pressure and deformation rates. To simulate such a process, the polymeric matrix is treated as a non-Newtonian, viscoelastic melt. The modeling of such melts is done with the anisotropic molecule movement tensor generalization of the Maxwell Model for high deformation rates. The viscoelastic flow simulations are done with DEVSS stabilization techniques and an ALE based dynamic mesh Method. In this work we present simulations in order to show the difference between classical approaches using a generalized Newtonian viscosity to model the melt and the used viscoelastic models. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

CFD-based predictive control of melt temperature in plastic injection molding

A unique method of coupling computational fluid dynamics (CFD) to model predictive control (MPC) for controlling melt temperature in plastic injection molding is presented. The methodology is based on using CFD to generate, via open-loop testing, a temperature and input dependent system model for multi-variable control of a three-heater barrel on an injection molding machine. Results clearly show the benefit of temperature and input dependent system models for MPC control, and that CFD can be used to dramatically reduce the time associated with open-loop testing through physical experiments.     

Optimization of the injection molding process for short-fiber-reinforced composites

A fast and effective methodology integrating the finite-element and Taguchi methods is presented to determine the optimal design conditions of the injection molding process for short-fiber-reinforced polycarbonate composites. The finite-element-based flow simulation software, M-flow, was employed to simulate the molding process to obtain the fiber orientation distributions required. The Taguchi optimization technique was used to identify the optimal settings of injection molding parameters to maximize the shear layer thickness. The effects of four main parameters — the filling time, melt temperature, mold temperature, and injection speed — on the fiber orientation or the shear layer thickness were investigated and discussed. It is found that the dominant parameter is the filling time. The best levels of the four parameters to acquire the thickest shear layer are also identified.     

Effect of process parameters on injection compression molding of pickup lens

The residual stresses and shrinkages of pickup lens in injection compression molding are investigated in this study. It was realized that the behavior of residual stresses in injection compression molding parts was affected by different process conditions such as melt temperature, mold temperature, compression pressure and time. Moldings under different conditions were numerically investigated to study the effects of the process conditions on the residual stresses and shrinkage of a pickup lens with large thickness variations. The mold temperature and compression were found to be the most important factors that affect the shrinkage of lens in the thickness direction, resulting in surface profile deviation. The effect of heat transfer coefficient of the mold wall used in the molding simulation was also discussed.     

Modeling and simulation of plasma jet by lattice Boltzmann method

In order to find a simple and efficient simulation for plasma spray process, an attempt of modeling was made to calculate velocity and temperature field of the plasma jet by hexagonal 7-bit lattice Boltzmann method (LBM) in this paper. Utilizing the methods of Chapman–Enskog expansion and multi-scale expansion, the authors derived the macro equations of the plasma jet from the lattice Boltzmann evolution equations on the basis of selecting two opportune equilibrium distribution functions. The present model proved to be valid when the predictions of the current model were compared with both experimental and previous model results. It is found that the LBM is simpler and more efficient than the finite difference method (FDM). There is no big variation of the flow characteristics, and the isotherm distribution of the turbulent plasma jet is compared with the changed quantity of the inlet velocity. Compared with the velocity at the inlet, the temperature at the inlet has a less influence on the characteristics of plasma jet.     

Numerical simulation of a two-phase melt spinning model

We consider a two-phase model of melt spinning including flow induced crystallization. Introducing slight modifications in the model we perform numerical simulations on it. We present comparison of our velocity profiles with the experimental profiles provided by the company Freudenberg & Co.     

Modelling and simulation of moving interfaces in gas-assisted injection moulding process

The mathematical models of gas–liquid two-phase flow are introduced, in which the multi-mode eXtended Pom–Pom (XPP) model is selected to predict the viscoelastic behavior of polymer melt. The gas-penetration process is simulated using Level Set/SIMPLEC methods, which can capture the moving interfaces at different time, including the gas–melt interface and the melt front. The physical features such as velocity, temperature and elasticity are described at different time. The influences of gas delay time and injection pressure on gas-penetration time and penetration length are analyzed. The numerical results show that the Level Set/SIMPLEC methods can precisely trace the two moving interfaces in gas-penetration process, the fractional coverage increases at very low Deborah numbers, while at higher Deborah numbers the fractional coverage decreases, and the penetration length is affected significantly by gas delay time and injection pressure.     

Modeling teletraffic arrivals by a Poisson cluster process

In this paper we consider a Poisson cluster process N as a generating process for the arrivals of packets to a server. This process generalizes in a more realistic way the infinite source Poisson model which has been used for modeling teletraffic for a long time. At each Poisson point Γ _j , a flow of packets is initiated which is modeled as a partial iid sum process , with a random limit K _j which is independent of (X _ji ) and the underlying Poisson points (Γ _j ). We study the covariance structure of the increment process of N. In particular, the covariance function of the increment process is not summable if the right tail P(K _j > x) is regularly varying with index α∊ (1, 2), the distribution of the X _ji ’s being irrelevant. This means that the increment process exhibits long-range dependence. If var(K _j ) < ∞ long-range dependence is excluded. We study the asymptotic behavior of the process (N(t)) _{t≥ 0} and give conditions on the distribution of K _j and X _ji under which the random sums have a regularly varying tail. Using the form of the distribution of the interarrival times of the process N under the Palm distribution, we also conduct an exploratory statistical analysis of simulated data and of Internet packet arrivals to a server. We illustrate how the theoretical results can be used to detect distribution al characteristics of K _j , X _ji , and of the Poisson process. AMS Subject Classifications Primary—60K30; Secondary—60K25 A large part of this research was done with support of Institut Mittag-Leffler of the Royal Swedish Academy of Sciences when the authors participated in the Fall 2004 program on Queuing Theory and Teletraffic Theory. Mikosch’s research is also partially supported by MaPhySto, the Danish research network for mathematical physics and stochastics and the Danish Research Council (SNF) Grant No 21-04-0400. Samorodnitsky’s research is also partially supported by NSF grant DMS-0303493 and NSA grant MSPF-02G-183 at Cornell University. González-Arévalo’s research is partially supported by BoRSF grant LEQSF(2004-2007)-RD-A-31 at the University of Louisiana at Lafayette.     

Comparative estimate of the molding capacities of injection molding machines with plunger and screw plastication

An analysis of the mold filling process, based on the equation of nonisothermal flow of an amorphous polymer melt, shows that for thin moldings the molding capacity of the machine, estimated as the maximum shot length, has a limit that does not depend on the pressure at the mold inlet and is determined by the flow rate of the polymer in the mold. As shown by an analysis of the process of compaction of the polymer in the system preceding the mold, this flow rate is many times less for plunger plastication, which is responsible for the reduced molding capacity of plunger machines. The effect can be eliminated by compressing the polymer before injecting it into the mold.Moscow Institute of Chemical Machine Building. Translated from Mekhanika Polimerov, No. 2, pp. 367–372, March–April, 1970.     

Modelling and Simulation of solidification processes in polymer melt flows

This work deals with the modelling and simulation of solidification processes in polymer melt flows. Two models describing the latent heat and the rheological behaviour were implemented in a finite volume code. The models are empirical and their parameters are identified using experimental results obtained from investigations with a rotational rheometer and a differential scanning calorimetry. First results of the simulation of a solidifying channel flow are shown. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Dynamic modelling of die melt temperature profile in polymer extrusion: Effects of process settings,screw geometry and material

Extrusion is one of the major methods for processing polymeric materials and the thermal homogeneity of the process output is a major concern for manufacture of high quality extruded products. Therefore, accurate process thermal monitoring and control are important for product quality control. However, most industrial extruders use single point thermocouples for the temperature monitoring/control although their measurements are highly affected by the barrel metal wall temperature. Currently, no industrially established thermal profile measurement technique is available. Furthermore, it has been shown that the melt temperature changes considerably with the die radial position and hence point/bulk measurements are not sufficient for monitoring and control of the temperature across the melt flow. The majority of process thermal control methods are based on linear models which are not capable of dealing with process nonlinearities. In this work, the die melt temperature profile of a single screw extruder was monitored by a thermocouple mesh technique. The data obtained was used to develop a novel approach of modelling the extruder die melt temperature profile under dynamic conditions (i.e. for predicting the die melt temperature profile in real-time). These newly proposed models were in good agreement with the measured unseen data. They were then used to explore the effects of process settings, material and screw geometry on the die melt temperature profile. The results showed that the process thermal homogeneity was affected in a complex manner by changing the process settings, screw geometry and material.     

Modeling and simulation of a gas distribution pipeline network

This research study focuses on the modeling and simulation of a gas distribution pipeline network with a special emphasis on gas ducts. Gas ducts are the most important components of such kind of systems since they define the major dynamic characteristics. Isothermal, unidirectional flow is usually assumed when modeling the gas flow through a gas duct. This paper presents two simplified models derived from the set of partial differential equations governing the dynamics of the process. These models include the inclination term, neglected in most related papers. Moreover, two numerical schemes are presented for the integration of such models. Also, it is shown how the pressure drop along the pipe has a strong dependency with the inclination term. To solve the system dynamics through the proposed numerical schemes a based MATLAB-Simulink library was built. With this library it is possible to simulate the behavior of a gas distribution network from the individual simulation of each component. Finally, the library is tested through three application examples, and results are compared with the existing ones in the literature.     

Establishment of non-negative constraint method as a robust and efficient first-order reliability method

In structural reliability analysis, computation of reliability index or probability of failure is the main purpose. The Hasofer–Lind and Rackwitz–Fiessler (HL-RF) method is a widely used method in the category of first-order reliability methods (FORM). However, this method cannot be trusted for highly nonlinear limit state functions. Two proposed methods of this paper replace the original real valued constraint of FORM with a non-negative constraint, in all steps and during the whole procedure. First, the non-negative constraint is directly used to construct a non-negative Lagrange function and a search direction vector. Then, the first- and second-order Taylor approximation of the non-negative constraint are employed to compute step sizes of the first and second proposed methods, respectively. Contribution of the non-negative constraint and the effective approach of determining step sizes have led to the efficient computation of reliability index in nonlinear problems. The robustness and efficiency of two proposed methods are shown in various mathematical and structural examples of the literature.     

Modeling binary alloy solidification by a random projection method

This paper addresses the numerical modeling of the solidification of a binary alloy that obeys a liquidus–solidus phase diagram. In order to capture the moving melting front, we introduce a Lagrange projection scheme based on a random sampling projection. Using a finite volume formulation, we define accurate numerical fluxes for the temperature and concentration fields which guarantee the sharp treatment of the boundary conditions at the moving front, especially the jump of the concentration according to the liquidus–solidus diagram. We provide some numerical illustrations which assess the good behavior of the method: maximum principle, stability under CFL condition, numerical convergence toward self‐similar solutions, ability to handle two melting fronts.     

Mathematical simulation of a reflux mass-transfer process

We study a numerical-analytic method of solving an initial-boundary value problem for a quasilinear system of differential equations of parabolic type with initial condition given by the Dirac delta function. One figure. Bibliography: 6 titles. Translated fromProblemy Matematicheskoi Fiziki, 1998, pp. 209–213.