ICONE23-1797 INVESTIGATION OF CONVECTION HEAT TRANSFER OF SUPERCRITICAL WATER USING ATHLET SYSTEM CODE
Bibliographic record
Abstract
SuperCritical Water-cooled Reactors (SCWRs) are one of six Generation-IV nuclear-reactor concepts. They are expected to have high thermal efficiencies within the range of 45 - 50% owing to the reactor's high pressures and outlet temperatures. Efforts have been made to study the supercritical phenomena both analytically and experimentally. The thermal-hydraulic computer code ATHLET (Analysis of THermal-hydraulics of LEaks and Transients) is used for analysis of anticipated and abnormal plant transients, including safety analysis of Light Water Reactors (LWRs) and Russian Graphite-Moderated High Power Channel-type Reactors (RBMKs). The range of applicability of ATHLET has been extended to supercritical water by updating the fluidand transport-properties packages, thus enabling a transition from subcritical to supercritical fluid states. In previous work, the applicability of ATHLET code to predict supercriticalwater behaviour in various heat-transfer conditions was assessed, and it was concluded that ATHLET can be used to develop preliminary design solutions for SCWRs. In this work, experimental investigations of the local convection heat transfer of supercritical water in a 10 mm diameter bare tube are presented for upward flow for low and moderate mass flux ranges (200 kg/m^2s and 500 kg/m^2s, respectively). The effects of heat flux, the influence of buoyancy and other flow parameters are investigated to further understand the convection heat transfer of supercritical water. A numerical model in ATHLET is created to represent the experimental test section and the results for the inside-wall temperature are compared with the experimental data. Some of the empirical correlations used in the ATHLET simulations are able to capture trends; however, important phenomena like Deteriorated Heat Transfer (DHT) are not being accurately predicted. It is clear that further work is needed to understand the flow parameters and that govern the heat transfer of fluids at supercritical pressures and appropriate heat transfer correlations need to be developed accordingly.
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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".