Inverse Identification Of Elastic Moduli For 3D Printed PLA, Using Impulse Excitation Technique (IET)
Bibliographic record
Abstract
3D Printing has recently undergone extensive development due to its lower cost and flexibility. A number of studies have been carried out to determine 3D printed material properties. This study focuses on the determination of the dynamic properties for PLA. The PLA material is processed through the popular FDM method with three different build orientations. A vibration experiment is conducted to evaluate the first modal frequency and Young’s modulus. The results are then compared to the FEM modal analysis and finally the traditional tensile testing results. The anisotropy of the 3D printed components, mainly due to the density changes caused by voids and filament alignment, result in the variation of the Young’s modulus which is different than the homogenous bulk material. The calculated Young’s moduli values are very slightly higher than the tensile test results which is in conformance with the trend documented by earlier studies on similar printed materials using the same techniques
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".