Real-Time Digital-Twin of Thorium-Based Molten Salt Breeder Reactor for Closed-Loop Controller Testing Applications
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".