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Record W2049634099 · doi:10.1504/ijpse.2011.038943

Development of support tool for control design of nuclear power plant using hierarchical control chart (HCC)

2011· article· en· W2049634099 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Process Systems Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTroubleshootingSystems engineeringControl (management)Nuclear powerNuclear power plantControl engineeringProcess (computing)Hierarchical control systemAdvanced process controlEngineeringProcess controlControl systemReliability engineeringComputer scienceSoftware engineeringArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Control design of complex systems, such as nuclear power plants (NPP), is multidimensional problem that requires concurrent engineering environment. This paper presents the idea of integrating process and control models and associated knowledge using hierarchical control chart (HCC), which supports control activities throughout the analysis, design, and operation phases. Automated solution for implementing HCC is developed and presented using a selected case study of steam generator control design of nuclear power plant. Integrated knowledge architecture is presented to support different views during the control design stage: process design, control analysis, control design, control programming, operation, and troubleshooting. The proposed solution will provide better ways to structure and share control knowledge, which will reduce overall risks in the engineering process.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.861
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.229
Teacher spread0.208 · 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