Experimental Implementation of a Magnetic Levitation System for Laser-Directed Energy Deposition via Powder Feeding Additive Manufacturing Applications
Bibliographic record
Abstract
Magnetic levitation and additive manufacturing (AM) are two fields of significant interest in academic research. The use of non-contact forces for magnetic levitation techniques provides opportunities for adoption within the AM environment. The key goal of this article is to experimentally validate the implementation of a magnetic levitation system for Laser-Directed Energy Deposition via Powder Feeding (LDED-PF) Additive Manufacturing applications. Through simulations (conducted in ANSYS Maxwell) and experimental implementation, the levitation system’s stability is tested under a variety of different conditions. The experimental implementation highlights the feasibility of a magnetic levitation system for LDED-PF applications. The levitation system developed is capable of the suspension of non-magnetic materials. The system is also able to maintain stable levitation for extended periods of time. The incorporation of the levitation system into the AM environment may result in an increased maneuverability of non-clamped structures for AM deposition operations.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".