A NUMERICAL STUDY OF THE IMPACT OF MAKE-UP AIR VELOCITY ON THE SMOKE CONDITIONS IN AN ATRIUM
Bibliographic record
Abstract
This study is aimed at investigating the effects of make-up air velocity on the smoke conditions in an atrium.An atrium is a space in a building interconnecting many floors, which is commonly found in modern buildings for providing an attractive environment.These spaces pose a challenge for fire protection engineers due to the height (typically greater than 20 m), which decreases the effectiveness of automatic sprinkler systems.From the fire protection perspective, it is difficult to achieve the concept of floor compartmentation in a building with an atrium because smoke can easily migrate to the upper floors of the building in the event of a fire.Therefore, atria are commonly equipped with a smoke management system, such as natural ventilation or a mechanical system to manage smoke.This research numerically investigates the effect of make-up air on the smoke conditions in an atrium under different make-up air velocities and fire sizes.A total of twenty-four (24) simulations were conducted using the Fire Dynamics Simulator (FDS) to consider different scenarios of fire located at the center (axisymmetric), northwest corner and southeast corner of the atrium.Fire sizes of 1 MW, 3 MW and 5 MW along with different make-up air velocities of 1 m/s, 1.5 m/s, 2.5 m/s and 3.5 m/s were simulated to investigate their effect on smoke conditions the atrium.To compare the ability of FDS to accurately predict the fire conditions in an atrium resulting, the model was also used to simulate previously experimental full-scale fire tests conducted by Rafinazari and Hadjisophocleous [30].The results showed that the simulation predicted slightly higher temperatures and lower smoke layer heights when compared to the experimental tests.Overall, I appreciate my supervisor, Prof. George Hadjisophocleous, for his maximum support, and guidance throughout this program.I say a big thank you.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".