Effects of building height on the sound transmission in cross-laminated timber buildings – Airborne sound insulation
Bibliographic record
Abstract
Buildings constructed with cross-laminated timber (CLT) are increasing in interest in several countries. Since CLT is a sustainable product, it can help the building industry to reduce greenhouse gas emissions. Furthermore, buildings constructed with CLT are increasing in building height, thereby increasing the load on the junctions and structural building elements further down in the building. Several studies have investigated how the load impacts the sound transmission between apartments. The majority found that an increasing load could have a negative effect on the vertical sound insulation. However, the findings are limited to a few measurements or building elements, and the studies only investigate junctions with resilient interlayers. This article aims to investigate if the building height, and thereby the load, affect the vertical airborne sound insulation between apartments on different stories in different cross-laminated timber buildings, with or without the presence of viscoelastic interlayers, and to quantify the effect. Four CLT buildings with different building systems, building heights, and the presence of viscoelastic interlayers in the junctions were measured. The airborne sound insulation between different apartment rooms was measured vertically for stories on the lower and higher levels. The difference in airborne sound insulation was calculated separately for each building, and the measurements indicate that the vertical airborne sound insulation reduces further down in the buildings. Therefore, results show that increasing load, by an increasing number of stories, has a negative effect on the vertical airborne sound insulation.
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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 | 0.000 | 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) | 0.002 | 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".