Study on Neutronics and Thermalhydraulics Characteristics of 1200-MWel Pressure-Channel Supercritical Water-Cooled Reactor
Bibliographic record
Abstract
Nuclear power becomes more and more important in many countries worldwide as a basis for current and future electrical energy generation. The largest group of operating nuclear power plants (NPPs) equipped with water-cooled reactors (96% of all NPPs) has gross thermal efficiencies ranging from 30–36%. Such relatively low values of thermal efficiencies are due to lower pressures/temperatures at the inlet to a turbine (4.5–7.8 MPa/257–293°C). However, modern combined-cycle power plants (Brayton gas-turbine cycle and subcritical-pressure steam Rankine cycle, fueled by natural gas) and supercritical-pressure coal-fired power plants have reached gross thermal efficiencies of 62% and 55%, respectively. Therefore, next generation or Generation IV NPPs with water-cooled reactors should have thermal efficiencies as close as possible to those of modern thermal power plants. A significant increase in thermal efficiencies of water-cooled NPPs can be possible only due to increasing turbine inlet parameters above the critical point of water, i.e., supercritical water-cooled reactors (SCWRs) have to be designed. This path of increasing thermal efficiency is considered as a conventional way that coal-fired power plants followed more than 50 years ago. Therefore, an objective of the current paper is a study on neutronics and thermalhydraulics characteristics of a generic 1200-MWel pressure-channel (PCh) SCWR. Standard neutronics codes DRAGON and DONJON have been coupled with a new thermalhydraulics code developed based on the latest empirical heat-transfer correlation, which allowed for more accurate estimation of basic characteristics of a PCh SCWR. In addition, the computational fluid dynamics (CFD) Fluent code has been used for better understanding of the specifics of heat transfer in supercritical water. Future studies will be dedicated to materials and fuels testing in an in-pile supercritical water loop and developing passive safety systems.
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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 | 0.000 |
| 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 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".