Characterization of cold metal transfer and conventional short-circuit gas metal arc welding processes for depositing tungsten carbide-reinforced metal matrix composite overlays
Bibliographic record
Abstract
Abstract This paper compares the processing characteristics of advanced CMT (cold metal transfer) and conventional GMAW-S (gas metal arc welding with short-circuit metal transfer) processes for depositing Ni-WC MMC (nickel-based metal matrix composites reinforced with WC) overlays. In contrast to common expectations, advanced CMT technology with mechanically assisted droplet transfer could not demonstrate significant advantages over the GMAW-S process; on the contrary, CMT exhibits marginal disadvantages in terms of carbide transfer efficiency, volume fraction of retained WC, and deposition rate. Some carbides originally contained in the core of the feed wire are blown away and expelled out of the processing zone leading to physical losses of WC particles during the deposition processes, which is more significant for the CMT process owing to much higher waveform cycle frequency and cyclic feed wire retractions. CMT exhibits superior waveform stability, better control over penetration depth, marginally lower dilution level, and exceptional arc stability. The main parameters affecting carbide transfer efficiency and volume fraction of retained WC are wire feed speed and travel speed for both processes; increased wire feed speed and travel speed generally lead to decreased carbide transfer efficiency and reduced volume fraction of retained WC. Shielding gas may have different effects on the outcomes for the CMT and GMAW-S processes. CMT overlays show comparatively higher W and lower Fe concentration in the matrix, while GMAW-S overlays show a higher concentration of Fe in the matrix (due to elevated dilution level) with marginally higher matrix microhardness and more herringbone-like secondary carbide precipitates.
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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".