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Record W2494884364 · doi:10.12943/anr.2012.00005

Measurements of the High Dose Rate Profiles Inside a Shutdown CANDU<sup>®</sup> Reactor

2012· article· en· W2494884364 on OpenAlexaffvenue
C. Jewett, Jimmy Chow, D. Comeau, G. Jonkmans, Berend Smit, B. Sur, D. Taylor, Shijing Yue

Bibliographic record

VenueAECL Nuclear Review · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsShutdownMonte Carlo methodNuclear engineeringRodDose rateMaterials scienceDetectorPoint (geometry)Computational physicsPhysicsOpticsEngineeringMathematicsMedical physics

Abstract

fetched live from OpenAlex

The positions of the components of a reactor can change over time, due to radiation damage, sagging, etc. Thus, it is important to determine their positions. To satisfy this requirement of the staff at the Point Lepreau Generating Station, a method to determine the positions of reactor components has been developed and demonstrated. This method combines the use of dose rate measurements and Monte Carlo simulations. It first involves measuring the high γ-ray dose rates as a function of position within a reactor. Then it entails comparing these measurements with Monte Carlo simulations. In order to perform such measurements, a silicon diode detector and a scan drive system have been developed. In 2009, measurements of the γ-ray dose rate profile of the shut down Point Lepreau Generating Station reactor were conducted. By comparing the locations of the local peaks in the dose rate data, it was possible to determine the distances between the steel reactor components. The measured data were then compared with Monte Carlo simulations to determine how precisely one could locate the positions of the adjuster rods. Using this technique, it was found that the retracted adjuster rods were 440 ± 60 mm below their designed positions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.049
GPT teacher head0.269
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes2
Has abstractyes

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