Development of a Neutronics–Thermal-Hydraulic Coupling Methodology to Support the Safety Analysis of Ghana Research Reactor-1
Bibliographic record
Abstract
Computational codes traditionally used to simulate transient conditions in research reactors are often overly conservative, potentially overestimating safety margins. This study addressed these limitations by developing a best-estimate plus uncertainty (BEPU) methodology to improve predictive accuracy in coupled neutronics–thermal-hydraulic safety analyses for research reactors. Using a high-fidelity BEPU simulation framework, the study analyzed a reactivity insertion accident (RIA) for the Ghana Research Reactor-1 (GHARR-1), focusing on the hottest and average coolant channels. This methodology incorporates an axial power profile from MCNP simulations to provide realistic input data for updating the PARET/ANL model under a small reactivity insertion of 3.8 milli-k.The results indicated that reactor power should not exceed 52 kW to preserve fuel cladding integrity. Peak fuel and clad temperatures remained safely below incipient melting thresholds, ensuring robust safety margins. The analysis also showed that the primary coolant temperature reached a maximum of 60°C, well below the boiling point, confirming operational safety.A stochastic uncertainty quantification approach was employed to propagate uncertainties in the input parameters. This analysis yielded a nominal power of 35 kW with a 95% confidence interval of ±0.64 kW, providing a more nuanced understanding of operational variability than the deterministic single-point estimate of 34 kW. By incorporating Monte Carlo sampling, this study enhances predictive accuracy and ensures that safety margins are statistically validated rather than conservatively assumed. This range enhanced confidence in the reactor’s performance under normal operating conditions.Under simulated RIA conditions involving an instantaneous 3.8-milli-k reactivity insertion, the BEPU analysis revealed a sharp power peak of 53 kW, highlighting the reactor’s potential behavior during reactivity excursions. A sensitivity analysis identified reactivity and initial reactor power as the most influential input parameters affecting key outputs, such as power and coolant temperature.This work demonstrated the utility of the BEPU approach in refining safety analyses, moving beyond conservative assumptions to deliver a more accurate and probabilistic understanding of reactor behavior under transient conditions. The study provides critical insights for defining safety thresholds and improving operational protocols in research reactor safety analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".