Wind Effect on External Fire Spread through Openings under the Protection of Horizontal Projections or Vertical Spandrels—A Numerical Study
Bibliographic record
Abstract
A numerical investigation has been conducted to analyse the effect of wind on the vertical spread of fire through a front opening in a building’s external walls. The study utilises a building geometry established from previous experimental work conducted by the National Research Council of Canada (NRCC). A horizontal projection or a vertical spandrel is introduced above the opening of the compartment of fire origin. The purpose of the projection or spandrel is to inhibit the vertical spread of the fire, following the relevant requirements in the Australian National Construction Code (NCC). A computational fluid dynamics (CFD) package for fire-driven fluid flow, namely the Fire Dynamics Simulator (FDS), is employed to simulate the fire behaviour. The FDS model is validated against the NRCC’s experimental results, and a good agreement is achieved. Winds from three horizontal directions (front wind is normal to the opening, side wind is parallel to the opening, and back wind is from behind the building) have been investigated, with speeds ranging up to 10 m/s for each wind direction. Front wind speeds below 1 m/s are found to slightly enhance the vertical spread of the fire, while speeds exceeding 1 m/s are inclined to promote horizontal spread. The impact of side wind on the vertical fire spread was also found to vary with wind speed. The increase in the speed of back wind influences flame buoyancy, resulting in an augmented vertical fire spread. Furthermore, the numerical results reveal that a vertical spandrel of 1100 mm height is less effective in preventing vertical fire spread through openings, compared to a 1100 mm deep horizontal projection. The study suggests that the fire safety design in reducing the hazard of vertical fire spread through openings in buildings’ external walls could be further improved if the effect of wind is considered.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".