Sulfide stress cracking assessment of low-alloy L80 casing steel in H<sub>2</sub>S environment
Bibliographic record
Abstract
Purpose This paper aims to evaluate the sulfide stress cracking (SSC) resistance of L80 casing steels with different alloying chemistries (e.g. Ti-B and Mn-Cr-Mo) by correlating the reduction in area ratio with the mechanical property, inclusion and carbide. Design/methodology/approach SSC tests were conducted in 5.0 Wt.% sodium chloride and 0.5 Wt.% acetic acid solution saturated with H2S using constant load tensile method. The microstructure and fracture morphology of the steel were observed using scanning electron microscope. The inclusion and carbide were identified by energy dispersive spectroscopy and auger electron microscope. Findings Among all the testing steels, electric resistance welding (ERW) L80-0.5Mo steel demonstrates the highest SSC resistance because of its appropriate mechanical properties, uniform microstructure and low inclusion content. The SSC resistance of L80 steels generally decreases with the rising yield strength. The fracture mode of steel with low SSC resistance is jointly dominated by transgranular and intergranular cracking, whereas that with high SSC resistance is mainly transgranular cracking. SSC is more sensitive to inclusions than carbides because the cracks are easier to be initiated from the elongated inclusions and oversized oxide inclusions, especially the inclusion clusters. Unlike the elongated carbide, globular carbide in the steel can reduce the negative effect on the SSC resistance. Especially, a uniform microstructure with fine globular carbides favors a significant improvement in SSC resistance through precluding the cracking propagation. Originality/value The paper provides the new insights into the improvement in SSC resistance of L80 casing steel for its application in H2S environment through optimizing its alloying compositions and microstructure.
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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".