Increasing Sound Insulation of Window with Add-on Systems & Various Insulating Glass Unit Configurations
Bibliographic record
Abstract
The acoustic performance of a building envelope is greatly dependent on the windows and other glazing elements. Windows represent a significant sound path for exterior noise to transmit into the interior space due to their relatively low mass. Replacement or upgrade of existing windows may be impractical due to heritage site, financial or investment considerations, and rental or condominium agreements. To combat noise infiltration in existing residential buildings, commercially available add-on systems can be incorporated to either the exterior or interior side of the windows. This research describes results of sound intensity measurements of five types of window add-on systems and their potential to reduce sound transmission through a standard size residential unplasticised polyvinyl chloride framed window. The effects of different add-on systems were investigated on three types of insulated glazing unit (IGU), double pane, double pane-acoustic and triple pane. All add-on systems exhibit frequency band dependent acoustic improvement from the baseline IGU. The add-on systems provide the most appreciable noise reduction when they are installed on the baseline double pane IGU, less increase performance on the double pane-acoustic and limited performance increase on the triple pane. In some instances when add-on systems are installed on either side of the double pane windows, the entire assembly acts as a triple pane IGU system with an additional air chamber created. Mass-air-mass-air-mass resonance may be found at low frequencies. Empirical measurements demonstrate the limits of the single number ratings, STC and OITC, which may indicated reduction in acoustic performance when there is a demonstrated increase in transmission loss at some 1/3 octave band frequencies. The information provides guidance in the selection of window add-on system for existing residential buildings that have high exposure to road traffic noise.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".