Comparative study of continuous and pulsed laser high-chromium steel (Fe-Cr-Ni-Mo-Mn) cladding
Bibliographic record
Abstract
Series of experiments of high chromium steel (Fe-Cr- Ni-Mo-Mn) laser cladding over a 316L substrate have been carried out in both pulsed and continuous modes, using an Yb-YAG disk laser. The investigation focused on the effects of cladding parameters such as laser pulse energy, duration and travel speed, on cladding properties including dimensions, microstructure and hardness. The different claddings obtained in this study were characterized in terms of microstructural changes, phase composition, and carbide distribution and morphology using Optical Microscopy (OM), Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). Also, the size and the orientation of the grains in the clad after rapid solidification have been observed by electron backscattered diffraction (EBSD). It was observed that the use of pulsed laser resulted in finer microstructure and higher hardness. Wear tests were performed using pin-on-disk device under argon to prevent sample oxidation, at room temperature for pulsed and continuous laser power. Different wear mechanisms were observed, with pulsed laser cladding and high duty cycle exhibiting better wear resistant. Indeed, the lowest average friction coefficient is obtained with pulsed laser and is relatively stable with the change in sliding time. The relationship between the scale of the dendritic network and the corresponding wear behavior has been discussed.
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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 | 0.000 | 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".