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Summer ’98 Volume 4.2 |
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Advances in process simulation technology
showcased at ANTEC ‘98 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 protocolOur 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. ANSYS Simulating Real Life: Software With No Boundaries
Conference and Exhibition. Aug. 17 - 19, Pittsburgh, PA. 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
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. 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 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, 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. Simulations and Applications of Injection-Compression
Molding (24), S.-C. Computer-Aided Gas-Assisted Injection-Molding of the Front
Cover of Motorcycle Effects of Complex Rib Distributions on Mold Filling and
Mechanical Properties Computer Simulation and Experimental Verification of Gas-Assisted
Injection Thermoforming Material Constants Identification for Thermoforming Simulation
(657), A. 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 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), 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. Cycle Time Predictions for the Rotational Molding
Process with and without MoId/ Part Separation (962), G. Gogos, X. Liu,
L. G. Olson
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