Wind Effects on Roofs with High-Profile Tiles: Experimental Study
Bibliographic record
Abstract
Hurricane wind–induced damage to the roofs of residential buildings has raised concerns regarding design provisions and construction practices. Current code provisions on wind loads on roofs are mainly based on testing of building models that do not include the architectural details of roofing materials. Past research has indicated that net pressures on roof tiles can differ significantly from external pressures on bare roofs and depend on wind direction, the location of the tile, and whether the eaves are sealed. This study presents experimental pressure measurements that confirm existing findings and provide more extensive results on wind loads on high-profile roof tiles. Four different roof models with bare and tiled roof decks were tested. Pressures on the external surfaces of the tiles, within the cavity space, and in the joint space between two overlapping tiles were measured to evaluate their effects on the net peak pressures on the tiles. Area-averaged peak pressure coefficients obtained for bare and tiled roof decks were found to differ significantly. To develop vulnerability curves pertaining to roof tile damage in residential buildings, the test results were complemented by additional pressure data obtained in a wind tunnel and tile resistance data obtained from static uplift tests. The vulnerability study showed that applying the net wind uplift loading on tiles rather than external surface pressures only resulted in increased roof tile damage. Results are expected to differ for tile shapes not considered in this study. The test protocols presented in this study may be used to help develop tile-specific design guidelines.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".