Application of Uncertainty Analysis in the Comparison of Void Fraction Calculations With Experiment
Bibliographic record
Abstract
Safety analysis computer codes are designed to simulate phenomena relevant to the assessment of normal and transient behaviour in nuclear power plants. In order to do so, models of relevant phenomena are developed and a set of such models constitutes a computer code. In accident or transient analysis the values of certain output parameters (margin parameters) are used to characterize the severity of the event. The accuracy of the computer code in calculating these margin parameters is usually obtained through validation and variation in the margin parameter is estimated through the propagation of variation in the code input. A method for estimating code uncertainty respect to a specific output parameter has been developed. The methodology has the following basic elements: (1) specification and ranking of phenomena that govern the behaviour of the output parameter for which an uncertainty range is required; (2) identification of models within the code that represent the relevant phenomena; (3) determination of the governing parameters for the phenomenological models and Identification of uncertainty ranges for the governing model parameters from validation or scientific basis, if available; (4) decomposition of the governing model parameters into related parameters; (5) identification of uncertainty ranges for the modelling parameters for use in Best Estimate Analysis; (6) design and execution of a case matrix; and (7) estimation of the code uncertainty through quantification of the variability in output parameters arising from uncertainty in modelling parameters. This methodology has been employed using simulations of Large Break Loss of Coolant Accident (LOCA) tests in the RD-14M test facility to calculate the uncertainty in the TUF thermal hydraulics code calculation of the coolant void fraction. The uncertainty has been estimated with and without plant parameters (parameters specific to the RD-14M test loop). The TUF coolant void fraction uncertainty without plant parameters was determined to be 0.08 while the uncertainty with plant parameters included was determined to be 0.11. The uncertainty value without plant parameters included is comparable to the uncertainty in the measurements (0.09). The uncertainty value with plant parameters included is larger than the variation in the bias (0.10) of the TUF calculation of void fraction. From these findings, it can be concluded that the estimated accuracy of the TUF code calculation of void fraction is consistent with the available experimental data.
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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 | 0.015 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".