Assessing the Effectiveness of Wall-Window Interface Details to Manage Rainwater—Selected Results from Window Installation to a Wall Sheathed in Extruded Polystyrene
Bibliographic record
Abstract
Abstract The detailing of wall-window interfaces and the consequences of defective installation of windows are an on-going concern in North America. This paper concerns laboratory evaluation of the water leakage performance of a select set of window-wall interface details. The details were for windows with mounting flanges installed in wood-frame walls sheathed with rigid extruded polystyrene foam. The tests were performed on a single full-scale test assembly in which two identical windows were installed by two similar but nonetheless different means. Each detail included a sill pan intended to collect water that gained entry into the assembly and thus was designed to be robust (tolerant of flaws). Tests were performed over a series of different water loading (spray) rates and over a series of different air pressure differentials at each spray rate. Air leakage rates through the window opening were monitored; they were controlled by a unique methodology. Leakage paths were introduced in the window frames, and these paths were alternatively blocked or opened to permit evaluation of the performance of the installation details under two different assumed conditions of window leakage. Air pressure distribution within the assemblies was monitored during spray testing. The wall assembly was designed to permit observation of water entry in it and to allow measurement of water entry to, or drainage from, various locations within the assembly. Results on water entry and management for the two wall-window interface configurations are given, and effectiveness of the details is discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".