Structural behavior of an ablated reactor pressure vessel wall with external cooling
Bibliographic record
Abstract
In a severe accident scenario of a nuclear power plant involving core meltdown and relocation to the lower head of the reactor pressure vessel (RPV), the vessel may undergo serious deformation and even failure due to extreme thermo-mechanical loads from the relocated core melt. Proper material models and detailed structural analysis are paramount in predicting the timing and mode of possible vessel failure. This paper presents a strain hardening creep model with optimal parameters to simulate the material behavior of the reactor steel 16MND5 under extreme thermo-mechanical loads. First, validations against two experiments, a tensile-creep test and the EU-REVISA RUPTHER #14 test, show that the proposed model is best overall compared to three previous models. Next, the creep model is implemented for the thermo-mechanical analysis of an ablated RPV under a severe accident scenario with external vessel cooling as a mitigation strategy. The effect of internal pressures from 3 to 50 bars is investigated with the assumption that the corners of the ablated part of the vessel have sharp corners. In this case, we found that the vessel fails above 40 bars. However, if we model the corners with varying smoothness or fillet sizes, we found significant delay in failure time and an increase in failure internal pressure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".