Numerical Analysis for Cavitation flow of the Depressurization Orifice of an Auxilary Feedwater Pump
Bibliographic record
Abstract
Nuclear power plant operators should check the performance of the pumps and valves that perform safety functions through In-Service Test(IST), and evaluate the degree of vulnerability over time.The Piping leakage occurred at the socket welding part of the Depressurization orifice of an Auxiliary Feedwater Pump in nuclear power plant of Korea.The operators of Nuclear Power plant suggested a Cavitation as the cause of the leakage by measuring the vibration of the pipe according to the flow rate.Cavitation is phenomenon that occurs in the low pressure part and is one of the main causes that impair the safety of the nuclear power plant system because it can occur in various devices such as pumps, valves, and measuring devices.From the regulatory point of view, the purpose of this numerical analysis is to verify operator's result by CFD.In this study, the Depressurization Orifice consisting of eight stages was modelled the same as the orifice used in the actual nuclear power plant, and was simulated for the effect of cavitation on this orifice using commercial CFD software, ANSYS Fluent with hexahedral grid system, generated by a grid generation software, ICEM-CFD.The flow of Auxiliary Feedwater Pump was assumed to be unsteady, incompressible, turbulent and multi-phase flow.Volume of Fluid(VOF) method and kw SST & k-e RNG Reynolds averaged Navier-stokes turbulent models was used for simulation.In this study, verification simulation was performed for the piping leakage caused by the cavitation in the pressure reducing orifice of the Auxiliary Feedwater Pump of nuclear power plant.As a result, the corrective action of Nuclear Power Plant operator for the leakage was confirmed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".