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Record W2064417176 · doi:10.1115/icone16-48750

Hardware-in-the-Loop Simulation Using Tricon v9 Safety PLC

2008· article· en· W2064417176 on OpenAlexafffund
Drew J. Rankin, Jin Jiang

Bibliographic record

VenueVolume 2: Fuel Cycle and High Level Waste Management; Computational Fluid Dynamics, Neutronics Methods and Coupled Codes; Student Paper Competition · 2008
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsWestern University
FundersUniversity Network of Excellence in Nuclear Engineering
KeywordsHardware-in-the-loop simulationProgrammable logic controllerShutdownNuclear power plantSuiteComputer scienceEmbedded systemController (irrigation)Control engineeringReliability engineeringSimulationEngineeringOperating system

Abstract

fetched live from OpenAlex

This paper presents the performance of shutdown system one (SDS1) implemented on a programmable logic controller (PLC) within real-time hardware-in-the-loop (HIL) simulation. SDS1 evaluation is focused on steam generator (SG) level low trip scenarios. A comparison of the findings with simulated expected plant operation is performed. An Invensys Triconex Tricon v9 safety PLC is interfaced to a real-time nuclear power plant (NPP) simulation suite (DarlSIM), replicating the operation of the Darlington NPP SDS1. Design basis accidents (DBA) associated with SDS1 regulatory standards are developed and applied to the two simulation environments. HIL simulation is a preferred method for testing systems prior to installation and is necessary to ensure proper SDS verification and validation. The performance of the Tricon v9 PLC, the HIL simulation platform and the two simulation environments are evaluated.

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)0.001
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0070.000

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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueVolume 2: Fuel Cycle and High Level Waste Management; Computational Fluid Dynamics, Neutronics Methods and Coupled Codes; Student Paper CompetitionSame topicReal-time simulation and control systemsFrench-language works237,207