Bibliographic record
Abstract
The pressure equalized rainscreen wall, considered as the most effective building envelope against wind induced rain penetration, requires continuous investigations to reach better performance. This research seeks the optimum pressure equalization process under external pressure conditions and wall parameters that have not previously been studied in detail. For this purpose, a single compartment full-scale wall model was built in a controlled facility at the University of Western Ontario. The cavity pressure response to external fluctuations was experimentally examined with respect to the rainscreen venting area ratio, under two types of real wind pressure distributions generated mechanically at zero degree incidence: 1) single pressure and, 2) pressure gradient caused by the application of three different signals varying horizontally across the rainscreen.\nAs the rainscreen venting area ratio increases, the pressure equalization performance improves, irrespective of the nature of the applied pressure, implying an increase in the critical damping frequency. However, an applied pressure gradient leads to a lower degree of pressure equalization at a constant venting area. Moreover, the change of the vent openings layout has an impact on the wall performance, mainly at low venting areas. Locating the vent openings at the bottom of the rainscreen gives better pressure equalization rather than distributing them between top and bottom.\nUsing a numerical model, the cavity pressure measurements were underestimated under a uniform pressure and overestimated when subject to a pressure gradient. The agreement in the frequency domain between experimental and predicted signals was satisfactory in the high frequency regions at high venting area ratios. However, transfer functions and phase angles were overpredicted at low venting rates. Based on numerical simulations, the cavity volume change does not significantly affect the performance of the model under an external pressure gradient. When a single pressure is applied, the pressure equalization is reduced at a larger cavity depth, which is only apparent at low venting areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".