Study of fire smoke movement from building integrated photovoltaic (BIPV)double skin façade (DSF) fires using helium gas
Bibliographic record
Abstract
Advanced building technologies such as building integrated photovoltaics (BIPVs) systems have been widely applied in new and existing constructions, in order to reduce energy consumption and electricity demand in buildings.Meanwhile they can cause a new critical challenge, i.e., fire safety issues.On the one hand, plume from the PV panel fires could spread into the buildings through the windows and ventilation openings.On the other hand, the risk of fire can be elevated by affecting the propagation of fire inside and outside the building.Furthermore, interfering with the smoke and venting system, firefighting operation, and electrical shock dangers.Most of the studies on the PV panels are to find the cause of failure, improving the cell efficiency, cost reduction and extracting maximum power, while there is the need to study the mechanism for smoke propagation as well.Applying BIPV on the building cause major changes in the traditional method of using structural components.These changes may include changes in the material, standard distances, gaps, and duties of elements, each of which can bring new fire safety issues.
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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 | 0.000 |
| 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) | 0.001 | 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".