MétaCan
Menu
Back to cohort
Record W4413120788 · doi:10.1109/tns.2025.3596969

Real-Time Digital-Twin of Thorium-Based Molten Salt Breeder Reactor for Closed-Loop Controller Testing Applications

2025· article· en· W4413120788 on OpenAlexafffund
Xinyu Zhao, Weiran Chen, Venkata Dinavahi

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2025
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsUniversity of Alberta
FundersAlberta InnovatesNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsNuclear engineeringThoriumMolten saltBreeder (animal)Controller (irrigation)Breeder reactorMaterials sciencePhysicsNuclear physicsEngineeringBlanketMetallurgyUranium

Abstract

fetched live from OpenAlex

Molten salt breeder reactors (MSBRs), which utilize molten fluoride salts as both fuel and coolant, are currently being researched and designed worldwide, offering inherent safety features, efficient fuel utilization, and the potential for thorium-based fuel cycles. Given the advanced development status of MSBRs, real-time emulation is essential for dynamic analysis studies, accommodating more detailed models and advanced control strategies. This article proposes a real-time digital-twin (RTDT) based on a hardware-in-the-loop (HIL) emulation on a field-programmable gate array (FPGA) for a multi-domain two-fluid MSBR model with a designed controller for validation and testing. A nonlinear explicit numerical solution with an appropriate step-size and ordinary differential equation (ODE) solver is carried out in a non-iterative fashion to achieve the required accuracy and real-time execution. The MSBR hardware emulation and closed-loop controller tests have been implemented on the parallel hardware architecture of the FPGA in real-time for dynamic analysis and performance evaluation. The FPGA-based hardware emulation has achieved an ultralow latency of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.34~\mu $ </tex-math></inline-formula>s, providing a remarkable 427-fold acceleration in faster-than-real-time (FTRT) performance. The designed controller performs well under transient and steady-state operating conditions, effectively stabilizing the MSBR system under perturbations, as validated on the RTDT.

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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.858
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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 teacher head, 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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Nuclear ScienceSame topicFault Detection and Control SystemsFrench-language works237,207