Investigation of Characteristic-Temperature Approaches for Heat-Transfer Correlations at Supercritical Conditions
Bibliographic record
Abstract
It is expected that the next generation of water-cooled nuclear reactors will operate at supercritical pressures (∼25 MPa) and high coolant temperatures (350–625°C). In support of the development of SuperCritical Water-cooled Reactors (SCWRs), research is currently being conducted for heat-transfer at supercritical conditions. Currently, there are no experimental datasets for heat transfer from power reactor fuel bundles to the fuel coolant (water) available in open literature. Therefore, for preliminary calculations, heat-transfer correlations obtained with bare-tube data can be used as a conservative approach. A number of empirical generalized correlations, based on experimentally obtained datasets, have been proposed to calculate Heat Transfer Coefficients (HTCs) in forced convective heat transfer for various fluids, including water, at supercritical pressures. These bare-tube-based correlations are available in various literature sources. There have been a number of methods applied to correlate heat transfer data. The most conventional approach, which accounts for property variations in the data, is to modify the classical Dittus-Boelter equation for forced convection. However, analysis and comparison of these correlations has shown that differences in HTC values can be up to several hundred percent. In general, the familiar correlations of Dittus-Boelter and Bishop et al. have used the bulk-fluid temperature approach for characteristic temperature properties evaluations. However, at high heat fluxes, fluid near the tube-wall will have a temperature close to that of the wall temperature. This might be significantly different from the bulk-fluid temperature. Therefore, another approach can be used based on the wall temperature as the characteristic temperature. The Swenson et al. correlation is based upon this approach. Finally, a third approach has been considered in which the film-temperature is used as the characteristic temperature (Tf = (Tw+Tb) / 2). McAdams et al. based their correlation for annuli on this approach. Therefore, the objective of this paper is to evaluate the three characteristic temperature approaches, (1) Bulk-fluid temperature approach; (2) Wall-temperature approach; and (3) Film-temperature approach, and determine which characteristic temperature method can most accurately predict supercritical water heat transfer coefficients. Both classical correlations and more recently developed correlations are considered in this investigation.
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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) | 0.001 | 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".