Dynamic Wind Uplift Performance of Thermoplastic
Bibliographic record
Abstract
Wind dynamics, on a conventional roofing system, lift the membrane and cause fluttering, introducing stresses at the attachment locations. To identify the component of the system that has the weakest resistance against wind uplift forces, a dynamic method of evaluating roofing systems is beneficial. A recent industry survey predicts significant growth for thermoplastic polyolefin #TPO# membranes. Among others, hot-air-weld ability is an advantage of the TPO. In mechanically attached TPO roofs, seams are formed by welding one side of the bottom sheet with the top sheet using hot-air machines. Advancements in welding technology have led to double-side weld procedures or encapsulated seams for the TPO membranes. Wind uplift evaluations are being carried out on the TPO systems with one-side weld and double-side weld. Experiments have been conducted at the dynamic roofing facility #DRF# of the National Research Council of Canada, using the SIGDERS #special interest group on dynamic evaluation of roofing systems# wind test protocol. Systems with double-side weld performed better than the systems with one-side weld. Use of double-side weld minimizes asymmetrical stress concentration and improves the wind rating of the mechanically attached TPO roofing systems.
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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) | 0.002 | 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".