Laser Powder Bed Fusion with Intentionally-Seeded Porosity for Prototyping of Powder Metallurgy Parts
Bibliographic record
Abstract
Laser powder bed fusion (LPBF) additive manufacturing technology was used to produce functional prototypes of powder metallurgy (PM) components from high carbon content, iron-based water-atomized powders. The melt pool modeling and design of experiment approaches were combined in order to determine the LPBF operation window allowing to print parts with components similar to the PM in terms of density, microstructure and mechanical properties. The size, morphology and distribution of processing-induced pores were evaluated using computed tomography, while a microstructure analysis was carried out using X-ray diffraction and scanning electron microscopy, and the mechanical properties were evaluated using tensile and unnotched Charpy testing. It was demonstrated that LPBF technology could effectively be used for the just-in-time manufacture of high-fidelity functional prototypes of PM parts from iron-based powders.
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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) | 0.000 | 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 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".