Effect of Wire Preheat and Feed Rate in X80 Steel Laser Root Welds: Part 1 — Microstructure
Bibliographic record
Abstract
Laser welding with cold versus hot wire feed was employed as a root pass to weld X80 pipeline steel. The influences of wire feed rate and preheat on the fusion zone microstructure were investigated. Increasing the wire feed rate helped generate acicular ferrite in the weld metal, and preheating the wire further suppressed the formation of bainite. The acicular ferrite in the upper region of the fusion zone was finer than that in the lower region, which was due to an increase in nucleation sites available. Five fill and cap passes were applied by gas metal arc welding to fill the remaining top part of the groove. Compared to arc welding with a higher heat input, laser welding led to finer prior austenite grains and smaller bainite packet size in the coarse-grained heat-affected zone and limited the formation of martensite-austenite constituents in the intercritically reheated coarse-grained heat-affected zone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".