Reliability assessment of emergency auxiliaries of an NPP using an additional steam turbine under various modes of its utilization
Bibliographic record
Abstract
Abstract Under complete blackout of a station, it is possible to cool-down the VVER-1000 type reactors using the energy of residual heat release of the reactors. The calculations from past works showed in the context of Balakovo nuclear power plant, that a single low-power steam-turbine unit by utilizing the energy of residual heat release from one reactor is capable to provide electricity for two VVER-1000 power units, including the cases when the first circuit in one of the units is depressurized. This work is a continuation of the investigation of the general-station reserve systems for nuclear power plants own needs. The effectiveness of the joint installation of an additional multifunctional steam turbine and a mobile general-station diesel generator was investigated taking into account the results of a large research of the causes for not starting diesel generators at nuclear power plants, conducted by scientists from the USA and Canada, according to which the interval of the percentage of their non-start ranges from 1 to 3%. It is shown that the reliability of such concurrent redundancy of the NPP’s own needs meets the IAEA requirements. Also in the work, the reliability of the developed emergency power supply system was investigated in the conditions of the additional steam turbine stop during the night off-peak hours of the electrical load. Research has shown that this is not acceptable for the accepted conditions from a safety point of view.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".