Collaborative Research Drives Technology Development

1. Collaborative Research Drives Technology Development Peter K. Kennedy & Rong Zheng Presented at iMUG05 in Orlando FL, October, 2006

2. It Takes Time to Use a New Material Effectively • People use their experiences with other materials initially • Substitution of old with new • In time designs evolve that use the intrinsic advantages of a material • Requires understanding of material properties • Development of forming technologies • Understanding of forming technologies • Examples • Wood to Metal • Metal to Plastic

3. Wood to Metal - Substitution • Iron Bridge 1779

4. Optimized Metal • Sydney Harbour Bridge 1932

5. Metal to Plastic - Substitution • Electric Drill • Note use of texture

6. Metal to Plastic • Evolved Design • Some special features

7. Metal to Plastic • Highly Evolved Design

8. It Takes Time to Use a New Material Effectively • In time designs evolve that use the intrinsic advantages of a material • Requirement • Understanding of material properties • Wood -> Metal -> Plastic • Characterization of properties • Development of forming technologies • Understanding of forming technologies • Simulation

9. Polymers – Relatively New Materials • Natural Polymers date back thousands of years • E.g. Rubber • Search for replacement of ivory • Billiard balls, pianos

10. Properties are temperature and time dependent Polymers can fail in different modes Processing determines properties Color wood and steel by painting Color polymers Create a different material Polymers – Very Different Materials

11. Why Are Polymers so Different? • Structure • Aspect ratio of 20,000 • Pasta • Processing determines properties

12. Getting Good Simulation Results • User Skill • Setting up of process/analysis conditions • Accuracy of geometry • Interpretation of results • Material Properties • Accuracy of Solution • Mesh • Mathematical models • Numerical methods

13. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and Temperature • Coefficient of expansion and modulus • pvT data • Long time behavior • Structural analysis

14. Our Approach • Moldflow • Modeling and implementation of models • Numerical methods • Implement best available models from academic/industrial collaborations • Rely on collaboration for some areas • Specialized measurement/equipment • Validation examples

15. Collaborators • SWIM, SCOOP, FISH (9 years) • ENSAM (France) (Shrinkage, morphology and properties) • Universite de Lyon (France) (Crystallization) • Universite de Nantes (France) (Thermal measurement and crystallization) • Solvay and Legrand (Belgium and France) • CRC Polymers (6 years) • Australian Nuclear Science and Technology Organization (ANSTO) (Synchrotron Studies of Crystallization and molecular orientation, Neutron scattering) • University of Sydney (Australia) (Crystallization, solidification and thermal conductivity) • Monash University (Australia) (Properties of polymers) • Technical University Eindhoven (Netherlands) • Fast cooling pvT data • Long term properties

16. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and Temperature • Coefficient of expansion and modulus • pvT data • Long time behavior • Structural analysis

17. Flow Analysis - Thermal Conductivity • Work by Venerus and Schieber et al. (IIT) • Anisotropic conductivity of PIB • Give melt a step shear of 8 in 75ms (shear rate ≈ 100s-1) • Measure diffusivity = • in shear direction • 20% increase • and normal to shear • 5% decrease

18. A Practical Example • Rough example • Gives • 17% increase in k in flow direction • 12% decrease in k transverse to flow

19. A Practical Example (Ctd.) • What about fiber filled material? • Glass is around 5 times as conductive • Random Case • kf =1.04 W/(K°m), km=0.2 W/(K°m) • Flowing Case • kf =1.04 W/(K°m)

20. A Practical Example (Ctd.) • Use Micromechanics to compute composite properties • Does it matter?

21. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and Temperature • Coefficient of expansion and modulus • pvT data • Long time behavior • Structural analysis

22. Flow Analysis - Viscosity • Amorphous Materials • No-flow is Tg • Viscosity goes up fast enough from Cross-WLF model • Semi crystalline • Viscosity does not go up fast enough • Use no-flow • Depends on cooling rate • Depends on flow

23. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and temperature • Coefficient of expansion and mechanical properties • Long time behavior • Structural analysis

24. Experimental Mold • ISO Plate size is 60mm x 60mm • Pressure transducer (4mm Ø) 47mm from gate (Kistler) • Restraints around edges • Delaunay et al. (Polym. Eng. Sci. 2000) 1.5mm (0.8mm) 3mm (1mm) 3mm Pressure transducer

25. Experimental Conditions

26. Pressure Evolution • Pressure at node 178

27. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and temperature • Coefficient of expansion and mechanical properties • pvT data • Long time behavior • Structural analysis

28. Temperature Calculation • Moldflow has used average specific heat for decades • Ok for energy balance • Not for temperature at specific time • Introduce crystallization kinetics in energy equation

29. Temperature Evolution • Delaunay et al. used heat flux to determine temperature field through thickness in situ • Delaunay et al. Polym. Eng. Sci. 2000 • Between 10 and 15 seconds increase in temperature due to crystallization

30. Material Data for Simulation • Crystallization model as described • Viscosity function • Cross-WLF • Pressure dependant viscosity D3 = 2.0E-7. • Specific heat and conductivity • Delaunay et al. Polym Eng. Sci. 2000 • Density from pVT

31. Temperature Evolution • Calculated Result

32. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and temperature • Coefficient of expansion and mechanical properties • pvT Data • Long time behavior • Structural analysis

33. Coefficient of Expansion and Modulus • Most simple (analytic) models require an isotropic matrix • Rosen Hashin – Coefficient of expansion • Tandon – Weng – Mechanical properties • Not suitable • LCP • Highly oriented material? • Can overcome with numerical method • Anisotropic matrix • Anisotropic inclusion

34. Thermo-mechanical Models (Ctd.) • Glass fiber filled LCP • Constituent properties

35. Thermo-mechanical Models (Ctd • Carbon fiber filled LCP • Constituent properties

36. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and temperature • Coefficient of expansion and mechanical properties • pvT Data • Long time behavior • Structural analysis

37. pvT Data • Crystallization depends on cooling rate and temperature • Also depends on shear Tc = 140°C / without shear : Tc = 140°C / g. = 0.5 s-1 / ts = 10s : Koscher & Fulchiron Polymer 2002 Tc = 140°C / g. = 5 s-1 / ts = 10s :

38. Commercial pVT data is static No shear effects New machine High cooling rate Shear treatment van der Beek et. al. Inter. Polymer Processing, 20, 111-120, (2005). pvT Data

39. pvT Data – Affect of Cooling Rate • Decrease in density for fast cooling • Decrease in “no-flow” temperature van der Beek et. al. Inter. Polymer Processing, 20, 111-120, (2005).

40. pvT – Affect of Shear • Shear has little effect on final density • Increases “no-flow” temperature van der Beek et. al. Inter. Polymer Processing, 20, 111-120, (2005).

41. pvT – Affect of Shear • Calculated and experimental shear effects • Wi = 1, 10 and 50 are 1.8, 17.7 and 88.6 1/s respectively. • Material is not identical van der Beek et. al. Inter. Polymer Processing, 20, 111-120, (2005).

42. Properties of Immediate Interest • Flow Analysis • Thermal conductivity • Viscosity • No flow • Warpage • Pressure and temperature • Coefficient of expansion and mechanical properties • pvT Data • Long term behavior • Structural analysis

43. Prediction of Failure – Short and Long Term • Vital for efficient product design

44. Long Term Property Prediction • Intrinsic deformation of polymers From E. Klompen, Ph.D. thesis, Technical University Eindhoven, 2005.

45. Ageing and annealing increases yield stress Material can be rejuvenated mechanically Ageing and Mechanical Rejuvenation Meijer and Govaert, Prog. Polym. Sci. 30, 915-938, 2005.

46. Long Term Property Prediction • Can predict yield stress from cooling history of the molding Govaert et al. Intern. Polymer Processing 20, 2005.

47. Getting Good Simulation Results • User Skill • Setting up of process/analysis conditions • Accuracy of geometry • Interpretation of results • Material Properties • Accuracy of Solution • Mesh • Mathematical models • Numerical methods

48. Conclusion • Collaborators provide invaluable assistance to development • Experimental data • Specialized measurements and techniques • New models • Much of this work will be implemented in commercial software • A consortium for post molding shrinkage and warpage is starting this year

49. Thank you • To you • Our collaborators • ENSAM, Univ. Lyon, Univ. Nantes, Solvay, Legrand • Crystallization, pvT, experimental data, thermo-mechanical models • Tech Univ. Eindhoven • pvT, Long term properties • Univ Sydney, ANSTO, Monash Univ. • Properties and crystallization • Univ. Leeds