Summer ’98 Volume 4.2

















Figure 1. Flow fronts in a printer component, using
three-dimensional simulation. Graphic courtesy
Moldflow Pty., Ltd.

 

 










































Figure 1. Apparatus for measuring biaxsial deformations

 

 

Figure 3. Picturre pasted on a 3D formed cup

 
Articles
 

Advances in process simulation technology showcased at ANTEC ‘98

ANTEC 98, held in Atlanta in May, saw interesting developments in the areas of CAE and material modeling for CAB. New analysis codes were demonstrated for fully three-dimensional simulation of the injection molding process. There were novel developments in the simulation of the rotational molding, thermoforming and blow molding processes. New material modeling techniques were introduced for the simulation of thin wall injection molding. Novel techniques for the measurement of extensional viscosity and biaxial stress-strain behavior were also presented.

Injection Molding Simulation

The injection molding process has traditionally been simulated using a 2.5D approach, a two-dimensional flow simulation with the behavior across the third direction (part thickness) being assumed to follow a pre-defined pattern. This approach has worked extremely well because injection molded parts are typically thin. Because of computational limitations, initial implementations of this scheme assumed symmetry across the part thickness and performed only a half gap thickness calculation. The newer codes implement a ‘full-gap thickness’ calculation to account for differences arising from nonuniformity of mold wall temperatures and other factors. The 2.5D situation fails when the part thickness is comparable with the planar (x-y) dimensions.

Fully three-dimensional simulations have become feasible with the widespread availability of high-speed computers. The paper of Friedl at al. discusses Moldflow’s implementation, which has shown the capability to predict unique 3D flow phenomena such as asymmetric flow fronts (Figure 1). The simulation is also able to predict edge effects that cannot be captured with 2.50 schemes. There were several papers addressing the complexities of simulating the thin wall molding process. Maloney and Poslinzki discussed the problems associated with this form of molding and showed that accounting for material shear degradation and pressure dependency of viscosity resulted in improved predictive capability. Papers by Mahishi and Dealy presented schemes to obtain the pressure dependency of viscosity.

Blow molding and thermoforming

Blow molding and thermoforming codes have also evolved in the past year with developments reported by T-SIM, Polyf low and NRC Canada. Spence and Hylton discussed the correlation between sag and creep effects. Novel developments were reported in the measurement of extensional viscosity including papers by Derdouri and Baird. Collier et al. published their findings on the use of an unlubricated hyperbolic die, and Christensen and Kjoer discussed the effect of pressure on the extensional viscosity.

Rotational molding

Olsen and Gogos of the University of Nebraska have introduced a new multidimensional finite element approach to study heat transfer in rotational molding. Their simulations will permit analysts to estimate cycle time and predict variations of plastic deposition in the mold.

Thermoforming, blow molding data

Datapoint Testing Services has started an experimental program to generate high temperature stress-strain properties and coefficient of friction data used in thermotorming and blow molding simulations. The study will investigate uniaxial and biaxial deformation. We invite readers who have an interest in these properties to participate in the development effort. Please contact Hubert Lobo for details.

Datapoint adds West Coast office, new personnel

A satellite office was recently established in Seattle to enhance our support of customers on the West Coast. Gary Timpe, who has been promoted to Western Regional Sales Manager, heads the office. Gary looks forward to meeting with our West Coast clientele.

Dat apoint Testing Services welcomes Walter Seleski as Senior Laboratory Technician. Wally’s 15 years of experience in extrusion have given him familiarity with a broad range of materials.

New PVT testing protocol

Our pressure-volume-temperature test protocol has been revised: isother-mal heating measurements are now standard Previously, our protocol called for isothermal cooling scans in accordance with the recommendations of some CAE packages. However, the cooling rate of such scans is much slower than the speed at which materials cool in molding situations. Slower cooling in semi-crytalline materials may cause an increase in crystallinity, and the resulting PVT data may overpredict shrinkage. Heating scans, in contrast, start with a molded part at room temperature, and provide a better measure of the final specific volume.

Upcoming events

ANSYS Simulating Real Life: Software With No Boundaries Conference and Exhibition. Aug. 17 - 19, Pittsburgh, PA.
Watch for our poster session.

SPE Thermoforming Division Conference. Sept. 19 -22, Nashville, TN. IBEC ‘98. Sept. 29 - Oct. 1, Detroit, Ml.

1998 C-MOLD North American Users Conference. Sept. 29 - Oct. 2. Orlando, FL.

ISO TC-61 Meeting. Oct. 5-9. Whistler, British Columbia.

Understanding the role of the material in thermoforming simulation


Figure 2 Thickness profile of a cup produced using plug assisting thermoforming. The left most part of the
graph corresponds to the cup bottom.

Thermoforming is characterized by large deformations of the polymeric material being processed. Computer simulation has been found to be a useful method to optimize the process. However, the simulation is complicated by the fact that an elastic material model cannot describe the thermoforming deformation precisely. Non-linear, time-dependent viscoelastic behavior has to be taken into account.

Earlier attempts to simulate thermoforming often used elastic models. The most popular of these was the Ogden model due to its ability to fit the non-linear stress-strain curve. This model has the serious limitation that it is unable to take into account the time and strain rate dependency of the deformation during the forming process and therefore cannot describe viscosity. This limitation has a serious impact when applying it to thermoforming simulation, It results in the inability to describe time-dependent sagging, stress relaxation, and especially plug assistance.

In our research, we used the K-BKZ model to describe viscoelasticity and large deformation. Details of the model are available from the authors. The parameters of this model were determined experimentally. The evaluation was performed using the T-SIM® simulation program.

Model parameters estimation

Measurements were performed on an Instron machine equipped with a specially developed apparatus (Figure 1) enabling biaxial deformations similar to those appearing during plug assisted thermoforming. During the tests, the measuring (upper) head moved down at con stant speed and the corresponding force was measured. The resulting force vs. deformation curves at various temperatures and speeds of deformation was used for fitting K-BKZ model parameters.

The K-BKZ model cannot be used directly to fit measured force-deformation data, as the true stresses and strains are unknown. A reverse engineering method was employed to find the material constants. A set of materials with variable parameters was used for simulations of the test. Calculated force-deformation curves were compared with the measured data and the best corresponding curve determined fitted material parameters.

Influence of material properties

Simulations of the thermotorming process were carried out using several different materials. The comparison of the resulting thickness profiles confirmed the prediction that the final shape and the final wall thickness distribution are strongly influenced by material properties (Figure 2).

Although material and friction may seem to play an almost arbitrary role in the thickness distribution of the formed product, reasonable predictions can be drawn out of the simulation. The necessary condition is. of course, good knowledge of the material parameters given by K-BKZ model with an appropriate damping function.

Image predistortion

Pro-distortion of images is an example of reverse engineering in the field of thermoforming plastic sheet with printed im ages. The objective is to design a picture on a flat sheet, so that once thermoformed, the image will appear true.

The images can be pasted on the 3D surface of the formed product using T-SIM built- in tools (Figure 3). This includes projection of the image from the planar or curved surface, as defined by user. Since T-SIM knows the deformation history of each particle on the sheet, it can track the backward deformation path and find the position of the particle on the initial flat sheet.

References are available upon request.

Karel Kouba and Petr Novotny are the founders of T-SIM CZ Ltd., Tr. T Bati 299, 764 22 Zlin, Czech Republic.

Datapoint Testing Services is working with T-SIM to create TestPaks for material properties used in T-SIM simulations. Call for details on the tests and pricing: toll-free (U.S.) l-888-DATA-4-CAE.

Articles discuss use of engineering properties in simulation

We’ve compiled a bibliography of papers presented at ANTEC ‘98 that are relevant to the use of engineering properties in simulation. Article numbers are given in parentheses.

Injection Molding Simulation

Importance of Volume Relaxation in the Prediction of Residual-Stresses Buildup (9), H. Ghoneim

Correlation of Spiral and Radial Flow Lengths for Injection-Molded Thermoplastic Parts (166), C. W. Fox, A. J. Poslinski, D. 0. Kazmer

Shrinkage Analysis of Molded Parts Using Neural Network (838), S. C. Lee, J. H.
Baek, J. H Youn

Modeling of the Effects of Mould Venting on the Injection Moulding Process (654), 0. M. Gao, S. Reymond. J. F. Hetu, A. Garcia- Rejon

Viscosity Pressure Dependence and Material Degradation Effects on Thinwall Mold Filling Simulation (713), R. P. Maloney, A. J. Poslinski

Material Characterization for Thin Wall Molding Simulation (613), M. Mahishi

Extensional Viscosity Modeling for Injection Molding Simulation (791). P. Brincat. K. Talwar, C. Friedl

The Influence of Polymer Melt Elasticity on the Mold Filiing Behavior—Experimental and Simulated Results (993), A. Niarchos. C. G. Gogos

Three-Dimensional Simulation of Plastic Injection Molding (794), K. Talwar, F. Costa, V. Rajupalem, L. Antanovski, C. Friedl

3D Mould Filling of a Transfer Sprocket (653), A. Garcia-Rejon, J.-F. Hétu, L. Pecora, 0. Khennache

On the PVT and Thermal Shrinkage for the Injection Molding of a Plastic Lens (435), R.-Y. Chang, Y.-C. Hsieh, C.-H. Hsu

Estimating Linear Shrinkage of Semi- crystalline Resins from Pressure-Volume-Temperature (PVT) Data (825), A. M. Shay, Jr., A. J. Poslinski, Y. Fakhreddine

Asymmetrical Simulation of Filling and Packing Stages of Injection Molding Process (793), A. Bakharev, D. Astbury

Mold Filling Imbalances in Geometrically Balanced Runner Systems (939), J. P. Beaumont, J. H. Young, M. J. Jaworski

Cooling Prediction of Non-Watered Copper and Steel Mold Cores (494), J. Shoemaker, C. Kietzmann, P. Engelmann,
E. Dawkins

Advanced Cooling System for Closure Molds (352), A. Bernhardt, D. Vettor

Optimizing Part and Mold Design Using CAE Technology (280), V. Travaglini

From Part Design to Product—One Case History (281), J. Golmanavich

Minimize Part Warpage by Integrated CAE Technology (432), R.-Y. Chang, Y.C. Chen, C.-H. Hsu, M.-H. Tsai

Injection Molding Hybrids

Simultaneous Sandwich Injection Molding: Simulation and Experiment (567), D.
J. Lee, A. I. lsayev, J. L. White

Simulations and Applications of Injection-Compression Molding (24), S.-C.
Chen, Y.-C. Chen, N.-T. Cheng, M.-S. Huang

Computer-Aided Gas-Assisted Injection-Molding of the Front Cover of Motorcycle
Headlight (433), R.-Y. Chang, S-C. [in, K.
C. Chen., C-H. Hsu, M.-H. Tsai

Effects of Complex Rib Distributions on Mold Filling and Mechanical Properties
of Gas-Assisted Parts (696), K. Cutright, 0. Becker, K. W. Koelling

Computer Simulation and Experimental Verification of Gas-Assisted Injection
Molding (505), 1. J. Wang. H. H. Chiang, X. Lu, L. Fong

Thermoforming

Material Constants Identification for Thermoforming Simulation (657), A.
Derdouri, R. Connolly, A. Khayat, E. Verron, B. Peseux

Experimental and Theoretical Study of the Thermoformability of Industrial Polymers (658), D. Laroche, F. Erchiqui

Rheological Studies of Commercial Thermoforming Materials (920), T. Sponce, D. Hy!ton

Finite Element Analysis of the Effect of Processing Conditions on Thermoforming (905), G. J. Nam, H. W. Rhee, J. W. Lee

Optimisation of the Thermoforming Process: A Few Industrial Examples
(795), 1. M. Marchal, N. P. Cl emeur, A. K.
Agarwal

Blow Molding

Verification of the Accuracy of Blow Molding Software to Predict Wall Thickness of the Actual Part after Processing (2068), M. A. Sabatos, A. D. Pfaff

Process Modelling and Optimization for the Blow Moulding of a Fuel Tank (173),
D. Laroche, K. K. Kabanemi, L. Pecora, A. W. DiRaddo, L. Savoni, A. Puempel

Blow Moulding of an Industrial Part: A Comparison between Experiments and Simulation (52), B. Debbaut, 0. Homerin, A. Goublomme, N. Jivraj

Material characterization

A High Pressure Melt Rheometer and Some Results for a LLDPE (594), F. Koran, J. M. Dealy

Measurement and Prediction of the First Normal Stress Difference and Creep Compliance of Polypropylene Resins by Using the Wagner Model (517), J. BonillaRios, R. Darby, J. M. Sosa

On the Melt Fracture of Polypropylene (300), R. L. Sammler, C. P. Bosnyak, R. J. Koopmans, M. A. Mangnus

Flow Visualisation for Extensional Viscosity Assessment (312). C. Nakason, M. Kamala, M. Martyn, P. D. Coates

Extensional and Shear Rheology of Metallocene-Catalyzed Polyethylenes (185), S. E. Bin Wadud, D. G. Baird

Pressure Effect on Extensional Viscosity (530), J. H. Christensen, E. M. Kjoer Ultrasonic Characterization and Rheology of Polymer Foams (136), A. Sahnoune, A. Hamel, L. Piché

Standard Test Procedures for Relevant Material Properties for Structural Analysis (824), G. G. Tranfina, J. T. Woods

Are Injection Molded Test Specimens Homogeneous and Representative? (650), B. Guenther, G. Bendrich, N. Mathis

Polymer Melts and Concentrated Solutions Elongational Viscosity (542), 0. Romanoschi, J. R. Collier, S. Petrovan, I. Negulescu

Rotational molding

Polymer Sintering and Its Role in Rotational Molding (181), C. T. Bellehumeur, J. Vlachopoulos

Axisymmetric Finite Element Models of Rotational Molding (863), L. G. Olson, G.
Gogos, V. Pasham, X. Liu

Cycle Time Predictions for the Rotational Molding Process with and without MoId/ Part Separation (962), G. Gogos, X. Liu, L. G. Olson