Damage Assessment of Urban Interface Masonry Buildings after a Severe Wildfire along with a Comparison of NRC-2018
Bibliographic record
Abstract
The wildland-urban interface (WUI) has emerged as a focal point of wildfire management and community resilience efforts worldwide. The WUI, defined as areas where settlement reaches natural landscapes, presents a unique set of challenges for wildfire mitigation. On the other hand, the performance of the buildings throughout the fire and the provision of proper fire safety measures for structural members is one of the essential aspects of the design of buildings and infrastructures. This study attempts to emphasize the seriousness of the wildfire effects on the WUI in the Mediterranean neighborhood, especially in Turkey. For this purpose, the efficiency of the extreme heat throughout the wildfire on masonry buildings in Manavgat, Turkey (July-August 2021) was investigated in terms of performance and structural damages. Failure mechanisms and the damages that occurred during the wildfire are reported for masonry buildings as the main structural system in this neighborhood. Commonly used technical documents of a national guide for WUI fires presented by the National Research Council Of Canada (NRC- 2018) were employed to compare the condition of the buildings. Turkish standards do not cover wildfire conditions in terms of the WUI buildings. The influences of the materials, the type of cladding, and various types of roofs were investigated in masonry buildings. For this purpose, 121 masonry buildings in Manavgat, Turkey were examined in terms of performance and damage. Furthermore, a comparison of the data with WUI-NRC (2018) is represented to investigate some serviceable recommendations based on the investigation to reduce damages in buildings subjected to wildfire. Finally, an introduction to have detailed written local WUI regulations for masonry buildings to have enough safety in terms of life and economy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".