A New Facility to Simulate Simultaneous Wind and Thermal Effects on Roofing Systems
Bibliographic record
Abstract
Abstract Roofing systems are exposed to wind pressures and thermal stresses. Through a North American roofing consortium (Special Interest Group for Dynamic Evaluation of Roofing Systems—SIGDERS) the National Research Council Canada fabricated a facility to evaluate roof assemblies under simultaneous wind and thermal effects. The overall objective of this paper is to present the commissioning process of the facility based on experimental investigations that were carried out on a single-ply roofing system with a PVC membrane. For this study, roofing system responses were measured under simulated simultaneous wind and heat/cold conditions. A systematic attempt also was made to quantify the system response and to characterize the membrane properties. This was performed on a cold-conditioned system as well as by subjecting the membrane samples to the same cold-conditioning program in a laboratory freezer. Membrane samples were characterized by mechanical and chemical methods. Comparison of laboratory-conditioned membranes and wind-tested systems revealed the effects of cold conditioning and wind loading. Neither the wind uplift nor the mechanical properties (tensile breaking strength, elongation at break, tear strength, and seam strength) nor the chemical properties (glass transition temperature and weight loss) were affected by the selected cold conditioning. Based on these findings, directives for further studies are presented for this ongoing project.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".