Evaluating FDM Process Parameter Sensitive Mechanical Performance of Elastomers at Various Strain Rates of Loading
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Bibliographic record
Abstract
To optimize the mechanical performance of fused deposition modelling (FDM) fabricated parts, it is necessary to evaluate the influence of process parameters on the resulting mechanical performance. The main focus of the study was to characterize the influence of the initial process parameters on the mechanical performance of thermoplastic polyurethane under a quasi-static and high strain rate (~2500 s−1). The effects of infill percentage, layer height, and raster orientation on the mechanical properties of an FDM-fabricated part were evaluated. At a quasi-static rate of loading, layer height was found to be the most significant factor (36.5% enhancement in tensile strength). As the layer height of the sample increased from 0.1 to 0.4 mm, the resulting tensile strength sample was decreased by 36.5%. At a high-strain rate of loading, infill percentage was found to be the most critical factor influencing the mechanical strength of the sample (12.4% enhancement of compressive strength at 100% as compared to 80% infill). Furthermore, statistical analysis revealed the presence of significant interactions between the input parameters. Finally, using an artificial neural networking approach, we evaluated a regression model that related the process parameters (input factors) to the resulting strength of the samples.
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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) | 0.000 | 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) | 0.000 | 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 it