Modelling of Aqueous CO2 Corrosion of Iron in Turbulent Pipe Flow
Bibliographic record
Abstract
Abstract Aqueous CO2 corrosion of iron in turbulent pipe flow is modelled with a two-dimensional low Reynolds number k-ε turbulence model by simultaneously solving the conservation equations for mass, momentum, kinetic energy of turbulence and turbulent energy dissipation rate, along with the concentrations of various dissolved species. The effect of slow homogeneous chemical reaction of CO2 hydration is incorporated into the model by including an extra source term in the transport equation for H2CO3. Other homogeneous chemical reactions are assumed to be in equilibrium with the equilibrium adjusted after each iteration. The cathodic reactions considered are the reduction of H2CO3, H+ and H2O. The anodic reaction is iron dissolution. An iterative procedure is employed to calculate CO2 corrosion rates. It involves the determination of surface concentrations of dissolved species and the fluxes of all the reacting species at the surface. The iteration ensures that mixed potential theory is satisfied on the surface and that the cathodic fluxes are balanced by the anodic fluxes at the surface. The results of parameter studies are compared to the previous experimental findings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".