Use of Carbon Steel Beads to Determine Microbially-Influenced Pitting Corrosion under Flow Conditions
Bibliographic record
Abstract
Abstract Microbially influenced corrosion (MIC) in oil and gas transporting and production facilities is caused predominantly by the activity of sulfate-reducing bacteria (SRB). Carbon steel coupons are commonly used to determine MIC-associated corrosion rates. In this study, spherical carbon steel beads (∅ = 0.238 cm), which had an average mass of 55.0 ± 0.3 mg, were used to monitor corrosion. In order to study and quantify SRB-mediated MIC under flow conditions, as observed in many oil and gas facilities and pipelines, aqueous medium containing oilfield SRB was pumped into an up-flow bioreactor containing 35 beads. The SRB-containing medium was the outflow of a continuous culture vessel. SRB activity was monitored by determining sulfate, and other metabolite concentrations. The general corrosion rate was 0.11 mm/yr, after 256 days of continuous flow. Bead mass ranged from 36.5 to 51.4 mg with an average of 44.0 ± 3.3 mg. Surface examination indicated deep pitting in the most heavily corroded beads. However, the significant 11-fold increase in standard deviation from 0.3 to 3.3 mg is also a proxy for the unevenness of corrosion, or pitting corrosion. Hence, an effective system for studying SRB-mediated general and pitting corrosion under flow conditions has been designed.
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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) | 0.001 | 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".