ICONE23-1377 HEAT LOSS FROM RE-ENTRANT FUEL CHANNEL IN A 1200-MW_<EL> PRESSURE CHANNEL SCWR
Bibliographic record
Abstract
Generation III and III+ reactors are currently in operation globally and Generation IV (Gen IV) reactor designs are being developed. There are six Generation IV nuclear systems under development worldwide, namely, Very High Temperature Reactor (VHTR), Molten Salt Reactor (MSR), Gas-cooled Fast Reactor (GFR), Sodium-cooled Fast Reactor (SFR), Leadcooled Fast Reactor (LFR) and SuperCritical Water-cooled Reactor (SCWR). Of these six systems, Canada has decided to pursue the SCWR as its choice for a Gen IV reactor. One major advantage of the SCWR is an increase in thermal efficiency from the 30-35% range of current nuclear power plants to approximately 40-45%. SCWRs operate well above the critical point of water at a pressure of 25 MPa and reactor outlet temperatures up to 650°C. Due to the operating conditions, current fuel-channel designs cannot be used in the SCWR and new fuel-channel design concepts are under development. One such concept is called the Re-Entrant Channel (REC). The REC is a vertical channel and consists of two tubes, the inner (flow) tube and the pressure tube. The inner tube is hollow and the fuel bundles and insulator are located in the pressure tube. An annulus is formed between the flow and pressure tubes. A perforated liner is used to protect the insulator from the fuel-string, and the pressure tube is in contact with the moderator. The coolant flows from the top of the channel to the bottom via the flow tube and then reverses its direction and flows upwards through the pressure tube. The objective of this work is to determine the heat loss from a REC for a generic 1200-MW_<el> SCWR. A onedimensional onedimensional numerical model was developed in MATLAB to calculate the temperature profiles, the heat transfer coefficients and the heat loss from the coolant to the moderator for a given set of flow, pressure and temperature boundary conditions. With the results from the numerical model, the design of the REC can be optimized to improve the efficiency.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".