Corrosion inhibition of carbon steel under two‐phase flow (water‐petroleum) simulated by turbulently agitated system
Bibliographic record
Abstract
Abstract The corrosion of carbon steel in single‐phase (water with 0.1N NaCl) and two immiscible phases (kerosene‐water) using turbulently agitated system was investigated. The experiments were carried out for Reynolds number (Re) range of 38 000 to 95 000 using circular disc turbine agitator at 40°C. In two‐phase system, test runs were carried out in aqueous phase (water) concentrations of 1% vol, 5% vol, 8% vol, and 16.4% vol mixed with kerosene at various Re. The effect of Re, percent of dispersed phase, dispersed droplet diameter, and number of droplets per unit volume on the corrosion rate were investigated and discussed. Test runs were carried out using two types of inhibitors: sodium nitrite of concentrations 20, 40, and 60 ppm and sodium hexapolyphosphate of concentrations 485, 970, and 1940 ppm in a solution containing 8% vol aqueous phase (water) mixed with kerosene (continuous phase) at 40°C for the whole range of Re. It was found that increasing Re increased the corrosion rate and the presence of water enhanced the corrosion rate by increasing the solution electrical conductivity. For two‐phase solution containing 8% vol and 16% vol of water, the corrosion rate was higher than single phase (100% vol water). The main parameters that play the major role in determining the corrosion rate in two phases were concentration of oxygen, solution electrical conductivity, and the interfacial area between the two phases (dispersed and continuous). Sodium nitrite and sodium hexapolyphosphate were found to be efficient inhibitors in two‐phase solution for the investigated range of Re.
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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 | 0.000 |
| 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 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".