Development and Validation of a Simplified Thermal-Hydraulics Solver for the Modelling of Boiling Water Reactor Fuel Channels in DONJON5
Bibliographic record
Abstract
RÉSUMÉ: Ce mémoire de recherche présente le développement, la vérification et la validation d’un nouveau solveur de thermohydraulique simplifiée pour la modélisation d’un canal de réacteur nucléaire à eau bouillante (REB) pour le code de simulation Open-Source de coeur Donjon5. L’objectif premier de cette recherche est d’adapter le module de thermohydraulique déjà existant THM: initialement conçu pour la modélisation des réacteur à eau pressurisée (REP) et CANada Deuterium Uranium (CANDU) aux BWR. Les améliorations principales résident dans la modélisation de la chute de pression le long du canal du combustible, la modélisation des écoulements diphasiques, des transferts de chaleurs associés et de l’ébullition le long du canal. Ce travail comprend une revue de littérature des modèles, des codes de CFD et de thermohydraulique simplifiés existant. La conceptualisation du modèle basée sur le drift flux modèle (DFM) est explicitée ainsi que le processus de développement du code. Le DFM utilisé permet de décrire de façon efficace les interactions entre les phases liquide et vapeur sans nécessiter de trop grandes capacités de calcul. On y résout les équations de conservation de la masse, de la quantité de mouvement et de l’énergie ajustées selon le DFM et résolues en 1D en utilisant la méthode des volumes finis pour une mixture liquide-vapeur. Afin de vérifier le solveur, des équations analytiques du problème simplifié ont été trouvées pour comparer les résultats. La validation du solveur à été obtenue en comparant la nouvelle version du module THM: au code de calcul multiphysique CFD GeN-Foam et aux résultats expérimentaux issus du benchmark OECD/NUPEC BFBT. Les résultats montrent de bons accords entre fraction de vide, température, pression et vitesse avec les références, bien que certains écarts soient observés, notamment au moment de l’ébullition sous-saturée. Ces écarts pourront faire l’objet de travaux futurs, notamment pour modéliser de façon plus précise le départ en ébullition. Une analyse de sensibilité et de performance a ensuite été réalisée afin d’évaluer l’intérêt du solveur dans un contexte industriel. Les contributions de ce travail incluent non seulement l’avancement des capacités du code Donjon5, mais aussi la promotion des outils open-source dans le domaine du génie nucléaire, conformément aux principes de la science ouverte. ABSTRACT: This master thesis presents the development, verification and validation of a new simplified thermal-hydraulics solver for modeling a boiling water nuclear reactor (BWR) channel for the Donjon5 open-source full core simulation code. The main objective of this research is to adapt the existing thermal-hydraulics module THM: initially designed for pressurised water reactor (PWR) and Canada Deuterium Uranium (CANDU) modelling to the BWR. The main improvements lie in the modelling of the pressure drop along the fuel channel, the modelling of two-phase flows, associated heat transfers and boiling along the channel. This work includes a literature review of existing models, CFD and simplified thermalhydraulic codes. The conceptualisation of the model is based on the drift flux model (DFM), and the code development process is explained. The DFM enables the interactions between the liquid and vapour phases to be described efficiently without excessive computing power. The conservation DFM version of the mass, momentum and energy equations are solved and solved in 1D using the finite volume method for a liquid-vapour mixture. In order to do the verification of the solver, analytical equations of the simplified problem were found to compare the results. The solver was validated by comparing the new version of the THM: module with the CFD GeN-Foam multiphysics calculation code and with experimental results from the OECD/NUPEC BFBT benchmark. The results show good agreement between void fraction, temperature, pressure and velocity with the benchmarks, although some discrepancies are observed, particularly at the time of undersaturated boiling. These deviations could be the subject of future work, in particular to model subcooled boiling more accurately. A sensitivity and performance analysis was then carried out to evaluate the solver’s interest in an industrial context. This work’s contributions include advancing the capabilities of the Donjon5 code and promoting open-source tools in nuclear engineering, in line with the principles of open science.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".