Validation of New Process Models for Large Injection-Molded Long-Fiber Thermoplastic Composite Structures
Bibliographic record
Abstract
This report describes the work conducted under the CRADA Nr. PNNL/304 between Battelle PNNL and Autodesk whose objective is to validate the new process models developed under the previous CRADA for large injection-molded LFT composite structures. To this end, the ARD-RSC and fiber length attrition models implemented in the 2013 research version of Moldflow was used to simulate the injection molding of 600-mm x 600-mm x 3-mm plaques from 40% glass/polypropylene (Dow Chemical DLGF9411.00) and 40% glass/polyamide 6,6 (DuPont Zytel 75LG40HSL BK031) materials. The injection molding was performed by Injection Technologies, Inc. at Windsor, Ontario (under a subcontract by Oak Ridge National Laboratory, ORNL) using the mold offered by the Automotive Composite Consortium (ACC). Two fill speeds under the same back pressure were used to produce plaques under slow-fill and fast-fill conditions. Also, two gating options were used to achieve the following desired flow patterns: flows in edge-gated plaques and in center-gated plaques. After molding, ORNL performed measurements of fiber orientation and length distributions for process model validations. The structure of this report is as follows. After the Introduction (Section 1), Section 2 provides a summary of the ARD-RSC and fiber length attrition models. A summary of model implementations in the latest research version of Moldflow is given in Section 3. Section 4 provides the key processing conditions and parameters for molding of the ACC plaques. The validations of the ARD-RSC and fiber length attrition models are presented and discussed in Section 5. The conclusions will be drawn in Section 6.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".