ICONE23-1731 NUMERICAL ASSESSMENT AND COMPARISON OF HEAT TRANSFER CHARACTERISTICS OF SUPERCRITICAL WATER IN BARE TUBES AND TUBES WITH HEAT TRANSFER ENHANCING APPENDAGES
Bibliographic record
Abstract
Computational Fluid Dynamics (CFD) is a numerical approach to model fluids in multidimensional space using the Navier-Stokes equations and databases of fluid properties to arrive at a full simulation of a fluid dynamics and heat transfer system. A numerical study on heat transfer to supercritical water (SCW) flowing in a vertical tube is carried out using the ANSYS FLUENT code and employing the SST k-ω turbulence model. The 3D mesh consists of a 1/8 section (45 ° radially) of a bare tube. The numerical results on wall temperature distributions under normal and deteriorated heat transfer conditions are compared to experimental results. The same geometry is then simulated with an orifice to study the effect of geometrical perturbation on the flow and heat transfer characteristics of SCW. The orifice is placed areas to test the effect on normal, deteriorated and enhanced heat transfer regimes. The flow effects and heat transfer characteristics will be studied around the appendages to arrive at a fundamental understanding of the phenomena related to supercritical water turbulence.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".