Long-Term Corrosion Behavior of Cr Alloyed Steels in Aqueous CO2/H2S Environments Containing Chlorides
Bibliographic record
Abstract
The present study was designed to evaluate the long-term corrosion behavior of 3Cr and 13Cr steels in a single-phase flow environment containing aqueous carbon dioxide (CO2), hydrogen sulfide (H2S), and dissolved chlorides (Cl-). Long-duration tests, each lasting 40 or 100 days, were conducted using a flow loop equipped with a Thin Channel Flow Cell. The experimental setup aimed to replicate field conditions with varying H2S concentrations over time and included surface conditioning in NaCl brine before exposure to the corrosive solution. The results indicated that 3Cr and 13Cr steels exhibited different uniform and localized corrosion behaviors. The 3Cr steel exhibited average corrosion rates ranging from 0.03 to 0.12 mm/y, depending on specific test conditions and H2S concentrations. A beneficial effect of preconditioning was noted, potentially related to the formation of corrosion product layers with higher amounts of chromium rich oxides. However, localized corrosion was found in 3Cr steel when exposed to an increased H2S concentration of 100 mbar, even if its surface was preconditioned and the H2S concentration was increased gradually throughout the test duration. The 13Cr steel demonstrated a more stable corrosion rate, maintaining an average rate of approximately 0.01 mm/y, even with increased H2S content. However, minor localized corrosion was still detected at low H2S concentrations.
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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) | 0.000 | 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 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".