CONVECTIVE MASS TRANSFER THROUGH AN UNREACTIVE POROUS DEPOSIT LAYER UNDER HIGH TEMPERATURE CONDITIONS
Bibliographic record
Abstract
Fe–Cr–Ni alloys have experienced localized degradation, such as stress-corrosion cracking (SCC), when used for steam generator tubes in nuclear power plants. The tube surface can be covered by a porous deposit layer resulting primarily from fouling. This porous layer acts as a barrier to the mass transfer for the chemical species in the main fluid to the tube surface. Thus, it influences the interfacial chemistry at the metal surface and the susceptibility of Fe–Cr–Ni alloys to SCC. While the chemistry of the main fluid can be controlled and monitored, this interfacial chemistry must be determined indirectly. Numerical models can be used to predict the interfacial chemistry and provide insight to SCC initiation and propagation. In the present work, a numerical model has been developed to calculate the mass-transfer rate of a chemical species, such as dissolved oxygen (DO), from main fluid to tube surface through an unreactive porous layer under single-phase liquid flow conditions. Major features of the model were validated against available literature data at room temperature (25 °C). The numerical results for high pressure (5 MPa) and high temperature (250 °C) conditions show that the effect of advection on the mass-transfer rate of DO through an unreactive porous layer dominates over that of diffusion.
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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 | 0.001 | 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".