Computational Fluid Dynamics Analysis of an Open-Pool Nuclear Research Reactor Core for Fluid Flow Optimization Using a Channel Box
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Bibliographic record
Abstract
A channel box installation in the IEA-R1 research reactor core was numerically investigated to increase fluid flow in fuel assemblies (FAs) and side water channels (SWCs) between FAs by minimizing bypasses in specific regions of the reactor core, which is expected to reduce temperatures and oxidation effects in lateral fuel plates (LFPs). To achieve this objective, an isothermal three-dimensional computational fluid dynamics model was created using Ansys CFX to analyze fluid flow distribution in the Brazilian IEA-R1 research reactor core. All regions of the core and realistic boundary conditions were considered, and a detailed mesh convergence study is presented. Results comparing both scenarios are presented in the percentage of use of the primary circuit pump. It is indicated that 21.4% of fluid bypass to unnecessary regions can be avoided with the channel box installation, which leads to the total mass flow from the primary circuit for all FAs increasing from 68.9% (without a channel box) to 77.6% (with a channel box). For the SWCs, responsible for cooling LFPs, an increment from 9.7% to 22.4%, avoiding all nondesired cross three-dimensional effects, was observed, resulting in a more homogeneous fluid flow and vertical velocities. It was concluded that the installation of a channel box numerically indicates an expressive mass flow increase and homogeneous fluid flow distribution for flow dynamics in relevant regions. This gives greater confidence to believe that lower temperatures, and consequently oxidation effects in LFPs, can be expected with a channel box installation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it