MétaCan
Menu
Back to cohort
Record W2327097929 · doi:10.12943/anr.2013.00005

Implementation of A Gibbs Energy Minimizer In A Fission-Product Release Computer Program

2013· article· en· W2327097929 on OpenAlexafffundvenueabout
D.H. Barber

Bibliographic record

VenueAECL Nuclear Review · 2013
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsAtomic Energy (Canada)Royal Military College of Canada
FundersCANDU Owners GroupAtomic Energy of Canada LimitedHydro-QuébecBruce Power
KeywordsNuclear fission productFission productsNuclideNuclear fissionBurnupComputer scienceNuclear engineeringSpent nuclear fuelFissionNuclear physicsChemistryPhysicsEngineeringNeutron

Abstract

fetched live from OpenAlex

SOURCE 2.0 is the Canadian computer program for calculating fractional release of fission products from the UO2 fuel matrix. In nuclear accidents, fission-product release from fuel is one of the physical steps required before radiation dose from fission products can affect the public. Fission-product release calculations are a step in the analysis path to calculating dose consequences to the public from postulated nuclear accidents. SOURCE 2.0 contains a 1997 model of fission-product vaporization by B.J. Corse et al. based on lookup tables generated with the FACT computer program. That model was tractable on computers of that day. However, the understanding of fuel thermochemistry has advanced since that time. Additionally, computational resources have significantly improved since the time of the development of the Corse model and now allow incorporation of the more-rigorous thermodynamic treatment. Combining the newer Royal Military College of Canada (RMC) thermodynamic model of irradiated uranium dioxide fuel, a new model for fission-product vaporization from the fuel surface, a commercial user-callable thermodynamics subroutine library (ChemApp), an updated nuclide list, and updated nuclear physics data, a prototype computer program based on SOURCE IST 2.0P11 has been created that performs thermodynamic calculations internally. The resulting prototype code (with updated and revised data) provides estimates of 140La releases that are in better agreement with experiments than the original code version and data. The improvement can be quantified by a reduction in the mean difference between experimental and calculated release fractions from 0.70 to 0.07. 140La is taken to be representative of “low-volatile” fission products. To ensure that the existing acceptable performance for noble gases and volatile fission products is not adversely affected by the changes, comparisons were also made for a representative noble gas, 85Kr, and a representative volatile fission-product, 134Cs. These nuclides have the largest dataset in the SOURCE 2.0 validation test suite. This improvement provides increased confidence in the safety margin for equipment qualification in Loss-of-Coolant Accidents with Loss of Emergency Core Cooling.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2013
Admission routes4
Has abstractyes

Explore more

Same venueAECL Nuclear ReviewSame topicNuclear Materials and PropertiesFrench-language works237,207