Thermal patterns on solid masonry and cavity walls as a result of positive and negative building pressures
Bibliographic record
Abstract
Air leakage occurs in a variety of different ways through all types of exterior walls. In cold or warm climates, air leakage is accompanied with moisture transport. This moisture transport when migrating through dew point temperatures, leads to moisture accumulation within wall assemblies. This moisture accumulation may result in premature deterioration and mould formation given appropriate prolonged environmental conditions. Commissioning of air barrier assemblies using infrared thermography is an effective means of locating areas of air leakage defects. Since the environmental conditions that commissioning or building condition inspections are carried out vary considerably, the resultant air leakage thermal patterns on wall surfaces vary accordingly. This paper will outline the various types of thermal patterns created by both positive and negative building pressures during exterior inspection of various types of masonry clad buildings. These thermal patterns can be extrapolated to similar naturally occurring air leakage thermal patterns created by wind, stack effect and lack of existing mechanical system pressurization. This paper will outline the variable thermal pattern conditions created by cavity wall construction in addition to homogeneous solid wall construction and face seal type assemblies.
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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) | 0.001 | 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".