Vibratory Powder Feeding for Powder Bed Additive Manufacturing Using Water and Gas Atomized Metal Powders
Bibliographic record
Abstract
Commercial powder bed fusion additive manufacturing systems use re-coaters for the layer-by-layer distribution of powder. Despite the known limitations of re-coaters, there has been relatively little work presented on the possible benefits of alternative powder delivery systems. Here, we reveal a feeding technology that uses vibration to control flow for powder bed additive manufacturing. The capabilities of this approach are illustrated experimentally using two very different powders; a 'conventional' gas atomized Ti-6Al-4V powder designed for electron beam additive manufacturing and a water atomized Fe-4 wt.% Ni alloy used in powder metallurgy. Single layer melt trials are shown for the water atomized powder to illustrate the fidelity of the melt tracks in this material. Discrete element modelling is next used to reveal the mechanisms that underpin the observed dependence of feed rate on feeder process parameters and to investigate the potential strengths and limitations of this feeding methodology.
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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 | 0.000 |
| 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 | 0.001 | 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 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".