Numerical analysis of the cladding layer forming characteristics under the different wire feed speed conditions in additive manufacturing with inclined substrate
Bibliographic record
Abstract
Additive manufacturing with inclined substrate often exists in the practical applications. Most of the studies about laser wire additive manufacturing (LWAM) are mainly focused on the condition with horizontal substrate. A dynamic model for the LWAM with inclined substrate is developed to analyze the cladding layer (CL) forming process under the different wire feed speed conditions. The effect of wire feed speed on the CL forming characteristics in the LWAM with inclined substrate is discussed. It is found that the molten pool (MP) length and the maximum height of CL are increased, and the transfer period is decreased with the increase in wire feed speed. When the wire feed speed is 35 mm/s, some shallow valleys formed in the middle part of CL cause the increase in the fluctuation range of CL height compared with that under 40 mm/s wire feed speed condition. The CL height keeps in the relatively stable status without the obvious fluctuation under 40 mm/s wire feed speed condition. As the wire feed speed is increased to 45 mm/s, the CL morphology indicates the characteristic with the obvious peak and valley, and the forming quality of CL is deteriorated seriously. The obtained results are beneficial for promoting the LWAM application with inclined substrate.
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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) | 0.000 | 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 | 0.001 | 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".