Real-Time Digital-Twin for Synergistic Interaction of SMRs and Sustainable Power Systems
Bibliographic record
Abstract
Amid the challenges of digitalization, coordination complexities, and uncertainty in integrating diverse energy sources, digital-twin technology and small modular reactors (SMRs) are increasingly emerging as cutting-edge tools and technical pathways to address these issues. Against this backdrop, this article proposes a modular, scalable real-time digital-twin (RTDT) and surrogate physical-twin (SPT) collaborative hardware framework that predicts and responds to anomalies six times faster-than-real-time, while also addressing simulation interface issues across multiple physics modalities. The proposed system, deployed on a multiembedded field-programmable gate arrays platform, facilitates communication via the Aurora 64b/66b protocol and gigabit Ethernet based on IEEE 802.3, evaluating the impact of latency and data integrity on real-time performance. The SPT case study explores interactions among SMRs, the IEEE 39-bus system, and the CIGRÉ B4 DC grid with wind farms. The RTDT-SPT platform highlights the advantages of integrating next-generation advanced nuclear technology, renewable energy, and digital management systems by enhancing the coordination of SMRs in primary and secondary frequency control, reactor-leading mode, and turbine-leading modes, effectively smoothing the volatility of wind power generation.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".