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Record W2058109049 · doi:10.1115/icone12-49102

Validation of Physics and Thermalhydraulics Computer Codes for Advanced CANDU Reactor Applications

2004· article· en· W2058109049 on OpenAlexaffabout
David J. Wren, N.K. Popov, V.G. Snell

Bibliographic record

Venue12th International Conference on Nuclear Engineering, Volume 3 · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsNatural uraniumModular designSoftwareQuality assuranceNuclear engineeringCoolantNatural circulationComputer scienceReliability engineeringSystems engineeringEngineeringUraniumMechanical engineeringNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Atomic Energy of Canada Ltd. (AECL) is developing an Advanced CANDU Reactor (ACR) that is an evolutionary advancement of the currently operating CANDU 6 reactors. The ACR is being designed to produce electrical power for a capital cost and at a unit-energy cost significantly less than that of the current reactor designs. The ACR retains the modular CANDU concept of horizontal fuel channels surrounded by a heavy water moderator. However, ACR uses slightly enriched uranium fuel compared to the natural uranium used in CANDU 6. This achieves the twin goals of improved economics (via large reductions in the heavy water moderator volume and replacement of the heavy water coolant with light water coolant) and improved safety. AECL has developed and implemented a software quality assurance program to ensure that its analytical, scientific and design computer codes meet the required standards for software used in safety analyses. Since the basic design of the ACR is equivalent to that of the CANDU 6, most of the key phenomena associated with the safety analyses of ACR are common, and the CANDU industry standard toolset of safety analysis codes can be applied to the analysis of the ACR. A systematic assessment of computer code applicability addressing the unique features of the ACR design was performed covering the important aspects of the computer code structure, models, constitutive correlations, and validation database. Arising from this assessment, limited additional requirements for code modifications and extensions to the validation databases have been identified. This paper provides an outline of the AECL software quality assurance program process for the validation of computer codes used to perform physics and thermal-hydraulics safety analyses of the ACR. It describes the additional validation work that has been identified for these codes and the planned, and ongoing, experimental programs to extend the code validation as required to address specific ACR design features that have impact on the physics and thermalhydraulics codes.

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)0.024
metaresearch head score (Gemma)0.075
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.075
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.044
GPT teacher head0.315
Teacher spread0.271 · 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
GenreMethods

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
Published2004
Admission routes2
Has abstractyes

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