1. Improved Fiber Orientation Predictions for Injection Molded Composites Charles L. Tucker III and Jin Wang Department of Mechanical and Industrial Engineering University of Illinois at Urbana-Champaign John F. O’Gara and Gabriel DeBarr Delphi Research Labs NSF/DOE/APC Workshop: The Future of Modeling in Composites Molding Processes June 9-10, 2004

2. Fiber Orientation Prediction: State of the Art Describe orientation using A =  pp  Orientation evolves according to Jeffery’s eqn. + interaction term Hele-Shaw or 3-D mold filling simulation gives velocity distribution, D, W p L x y z 2h2h

3. The Problem: Orientation at Short Flow Lengths Edge-gated strips, PBT 30% glass fiber Measure elastic modulus in flow (E 11 ) and crossflow (E 22 ) directions Predict modulus using measured or predicted fiber orientation W  L  2h (mm) Experimental (GPa) Meas. Orient. (GPa) Pred. Orient. (GPa) 76  279  3 E 11 8.89.18.6 76  279  3 E 22 4.64.44.3 75  125  3 E 11 7.67.58.6 75  125  3 E 22 5.44.84.3 2h W L E 11 E 22

4. Orientation Structure: End-Gated Plaque x z x z top bottom shell: flow-aligned core: random or cross-flow (depending on inlet) shell core midplane 2h2h bottommidplanetop

5. Predicted vs. Measured Orientation, Standard Model In short plaques, predicted core is too narrow Leads to over-prediction of E 11, under-prediction of E 22 –2 mm, slow fill 90 mm 80 mm A B C 1.5, 2.0, 3.0, 6.0 mm

6. Progress Toward a Better Model Hypothesis: fibers experience local strain that is lower than average –resin-rich “slip layers” absorb most of the strain –fibers follow Jeffery-type motion based on local strain rate Strain Reduction Factor (SRF) = (fiber strain rate / total strain rate)

7. Experiment vs. SRF Theory New theory with SRF=20 does a good job for short plaques over a range of thicknesses and filling speeds –80  90  2 mm –slow fill speed

8. Our simple SRF theory is not objective –does not behave sensibly in rigid-body rotation; need an objective version of the model Can only get SRF value by fitting experimental data –need a micromechanics theory to predict SRF Further Steps for an Improved Model flow rotates at 100 RPM if SRF = 20, fiber rotates at 5 RPM!

9. plate specimen “plate” measur. measr. measur. simul. Long-Fiber/Thermoplastic Composites : Predicted vs. Measured Orientation Data from Reinhard Hafellner, Advanced Polymer Engineering Leoben, Austria

10. Gaps: Processing of Injection Molded Composites Fiber orientation modeling –capture the transient behavior at short flow lengths –models for long-fiber thermoplastics (include migration, fiber breakage, bundle dispersion) –predict orientation model parameters ( C I, SRF) as function of fiber volume fraction, l/d,... –models tested in a variety of flow geometries Fiber orientation measurement methods –non-destructive –capture full 3-D orientation –use online –...

11. Gaps, continued Models for warp/shrink/residual stress –state of the art: predict warp within factor of 2 –reach quantitative accuracy (fiber orientation, matrix PVT,... ) –incorporate flow-induced crystallization of matrix