FRACTAL AND THERMAL MODELING OF FOULING DEPOSITS IN STEAM GENERATORS
Bibliographic record
Abstract
Most corrosion products carried by the feedwater ultimately set down on the steam generator tubes to form fouling deposits. These deposits impact the thermal efficiency of the heat exchanger. They usually hamper the heat transfer from the reactor coolant (primary circuit) to the feedwater (secondary circuit). But under certain circumstances, they may even promote it. The main objective of this study is to develop a comprehensive steam generator heat transfer model which takes into account the phenomena and processes that characterize the fouling deposits. The model is made up of two parts: a fractal model which estimates the micro-characteristics of the deposits and a heat transfer model which simulates the thermal conduction and boiling phenomena. A sensitivity analysis is performed to determine the most influential parameters, i.e., the deposit thickness or the deposit porosity. It is found that thin and porous deposit layers promote heat transfer whereas dense and thick deposit layers deteriorate it. The limits of the model are discussed and future work for its improvement is suggested.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".