Influence of MIG/MAG Welding Process on Mechanical and Pitting Corrosion Behaviors on the Super-Duplex Stainless Steel SAF 2507 Welded Joints
Bibliographic record
Abstract
The main objective of this research is to better understand the correlation between the constituent phases presented in the super-duplex steel SAF 2507 when it is under welding process by arc shielding gas MIG-MAG (Metal Inert Gas-Metal Active Gas). Conventional short circuit transfer and derivative STT (Surface Tension Transfer) using the 2594 welding wire as a filler metal and the effects on welding power in hardness, toughness and pitting corrosion are considered here. The results showed that the welding energy (Ew) changed the α/γ-phase’s balance and occasionally formed σ-phase in ferrite grain boundaries which led to changes in hardness, toughness and pitting corrosion resistance in molten zone (MZ), heat activated zone (HAZ) and metal base regions (MB). Furthermore, the increased amount of γ-phase improved the pitting corrosion resistance index (PRENγ) mainly in the MZ. This is due to decrease of α-phase fraction and formation of coarser grains, for higher welding energy. The toughness in the MZ decreased with less formation of γ-phase, coalescence of ferritic grains and localized formation of σ-phase, raising the hardness in the HAZ when the welding energy was lower.
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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".