Effect of Cold-Wire Addition in the TSAW Process on Microstructure and Mechanical Properties of the HAZ of X70 Microalloyed Pipeline Steel
Bibliographic record
Abstract
Microalloyed steels can achieve a good combination of strength and toughness through appropriate alloy design and thermomechanical controlled processing (TMCP). However, the mechanical properties can deteriorate as a result of the high heat input and thermal cycles that the steel experiences during welding. It is generally accepted that the portion of the heat affected zone (HAZ) adjacent to the fusion line, i.e., the coarse grain heat affected zone (CGHAZ), which is characterized by coarse grains and martensite-austenite (M-A) constituents, is the region with poorer toughness relative to the rest of the steel. In the present research work, modification to the conventional tandem submerged arc welding (TSAW) process is carried out by the addition of a cold wire during welding (CWTSAW), which induces changes to the geometry and properties of the weld joint. Microstructural analysis, mechanical property investigation and geometry analysis indicate overall improvement in the weld and the HAZ properties after cold wire addition. These improvements are explained in terms of an increase in the deposition rate and a decrease in the amount of heat introduced to the weldment. An X70 microalloyed steel was welded using both TSAW and CWTSAW processes. Charpy-V-notch impact testing and microhardness testing showed improvement in the HAZ mechanical properties for CWTSAW samples relative to TSAW samples. Microstructural analysis, using both optical microscopy and scanning electron microscopy (SEM), indicated the formation of finer prior austenite grains (PAG) and less M-A constituent within the CGHAZ of the CWTSAW samples. These improvements are due to lower actual heat introduced to the weldment and a relatively faster cooling rate.
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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".