Effect of arc current of GTAW process on microstructural changes, hardness and tribological properties of Fe/NiCrMo composite coating
Bibliographic record
Abstract
In order to improve hardness and wear resistance of St60 steel substrate, NiCrMo welding wire was coated on its surface using gas tungsten arc welding (GTAW) process.Welding characteristics were considered to create a coating with maximum hardness and wear resistance and minimum defects.The results showed that the microstructure of the composite coatings mainly contains of α-Mo, NiMo and blade phases.By increasing in the arc current from 90 to 110 A, porosity and non-uniformity in microstructure of the coatings increased and the sample coated with the arc current of 90 A showed a more uniform microstructure and fewer defects.The average hardness of the coatings was obtained in the range of 218-227 HB (substrate's hardness is approximately equal to 152 HB).The sample prepared with arc current of 90 A showed the least weight loss and the sample prepared with arc current of 110 A showed the greatest weight loss.The wear mechanism of the substrate was mainly abrasive wear and the wear mechanism of the coatings was mainly abrasive and adhesive wear, with the lowest wear products related to the sample prepared with arc current of 90 A and therefore, this sample showed the greatest wear resistance.
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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 | 0.000 | 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".