Computational Fluid Dynamics Modeling of Fire and Human Evacuation for Nuclear Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The nuclear industry has seen an increased use of computational fluid dynamics (CFD) technology as a high-fidelity tool for design-basis and beyond-design-basis accident simulations. Among its applications, CFD modeling of fire and smoke propagation in confined zones (e.g., a main control room (MCR)) is a promising approach, since detailed experimental investigation under various accident scenarios would be difficult. Egress analysis considering human behaviors is of significant importance to an effective accident mitigation strategy, and high-fidelity analysis tools now encompass these parameters in the simulation and design of emergency evacuations. In this study, the fire and smoke propagation in a MCR is modeled using the large eddy simulations (LES) code fire dynamics simulator (FDS), along with an evacuation module, EVAC to simulate the emergency egress under an electrical cabinet fire scenario. The FDS results presented in this paper constitute the first step at Canadian Nuclear Laboratories (CNL) in advancing the CFD modeling of fire and evacuation for nuclear applications.
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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 | 0.000 | 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 | 0.000 |
| 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 it