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Record W1974414232 · doi:10.1115/icone18-29779

CANDU Reactor Space-Time Kinetic Modeling for Load Following Control

2010· article· en· W1974414232 on OpenAlexafffundabout
Lingzhi Xia, Jin Jiang

Bibliographic record

Venue18th International Conference on Nuclear Engineering: Volume 1 · 2010
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsWestern University
FundersMcMaster University
KeywordsTransient (computer programming)Neutron fluxNeutron transportNuclear engineeringDelayed neutronMATLABControl rodNeutronNuclear reactorFlux (metallurgy)Control theory (sociology)Computer sciencePhysicsNuclear physicsNeutron temperatureMaterials scienceEngineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents the development of a three-dimensional space-time neutronic kinetic modeling of a CANadian Deuterium Uranium (CANDU) reactor for control system design and research, using a modal method. In this method, the reactor space-time neutron flux is synthesized by a time-weighted series of pre-calculated neutron flux modes. The modes are eigenfunctions of the governing neutron diffusion equation during reference steady-state operation. The Xenon effect has also been considered. The reactor model is then implemented within a simulation platform of CANDU6 reactor regulating system (RRS), in MATLAB/SIMULINK. Non-dimensionalized SIMULINK representation of the reactor kinetic modeling is established. Behavior of the reactor during a load following transient has been simulated using the developed reactor-modeling module. The simulation results prove the efficiency of the reactor modeling. Real-time three-dimensional neutron flux distribution during the transient analysis is represented.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.011
GPT teacher head0.207
Teacher spread0.196 · 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

Citations0
Published2010
Admission routes3
Has abstractyes

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Same venue18th International Conference on Nuclear Engineering: Volume 1Same topicNuclear reactor physics and engineeringFrench-language works237,207