ICONE19-43503 DEVELOPING A HEAT-TRANSFER CORRELATION FOR SUPERCRITICALWATER FLOWING IN VERTICAL TUBES AND ITS APPLICATION IN SCWRS
Bibliographic record
Abstract
This paper presents an analysis of new heat-transfer correlations developed for supercritical water flowing in vertical bare tubes. It is an extension of the previous work performed at the University of Ontario Institute of Technology. A large dataset within conditions similar to those of SuperCritical Water-cooled nuclear Reactors (SCWRs) was obtained from the Institute for Physics and Power Engineering (Obninsk, Russia). The experimental dataset was obtained in supercritical water flowing upward in a 4-m long stainless-steel vertical bare tube with 10-mm internal diameter. The data points were collected at pressure of about 24 MPa, inlet temperatures from 320 to 350℃, values of mass flux ranged from 200 to 1500 kg/m^2s and heat fluxes up to 1250 kW/m^2 for several combinations of wall and bulk-fluid temperatures that were below, at, or above the pseudocritical temperature. Previous studies have shown that existing correlations, such as the Dittus-Boelter, Bishop et al., and Jackson correlations, deviate significantly from experimental Heat Transfer Coefficient (HTC) values, especially, within the pseudocritical range. The Swenson et al. correlation provided a relatively improved fit for the experimental data, as compared to the previous three correlations within some flow conditions, but deviates from data within other conditions. Also, HTC and wall temperature values calculated with the FLUENT CFD code might deviate significantly from the experimental data, for example, the k-ε model (wall function). However, the k-ε model (low Reynolds numbers) shows better fit within some flow conditions. Therefore, a new empirical correlation based on the Swenson et al. approach was developed. In this approach, the majority of thermophysical properties are obtained at the wall temperature as opposed to those obtained at the bulk-fluid temperature in previous correlations, which is considered as the conventional approach. Statistical error calculations were performed using analytical and graphical techniques. Results showed that calculated wall temperatures according to the new correlation were within ±10% and HTC values were within ±25% for the analyzed dataset. The correlation was also compared against data from other datasets. The proposed correlation can be used: (1) for a preliminary heat-transfer calculations in SCWR fuel channels as a conservative approach; (2) for calculations of supercritical-water heat-transfer in heat exchangers in SCWR indirect-cycle concepts; (3) for calculations of heattransfer in heat exchangers for the co-generation of hydrogen at supercritical water NPPs; (4) for calculations of SCW heat-transfer in heat exchangers for other Generation IV reactor concepts with an indirect cycle; (5) for future comparisons with other independent datasets and with bundled data; (6) for the verification of computer codes for SCWR core thermalhydraulics; and (7) for the verification of scaling parameters between water and modeling fluids (CO_2, refrigerants, etc).
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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".