Investigating flanking in mass timber construction: Acoustic performance of continuous timber panels over demising walls with resiliently isolated toppings
Bibliographic record
Abstract
As mass timber construction gains in popularity and project design teams pursue optimized structural schemes and cost-effective designs, there has been a growing desire for Cross Laminated Timber (CLT) floor panels to maximize panel size. This offers structural benefits and constructability improvements, with fewer crane picks resulting in panels spanning across units. This has led to concerns and questions surrounding flanking sound transmission across a demising wall through the CLT panel to adjacent units. While ASTM E90 acoustic laboratory testing presents direct sound transmission measurements that does not include indirect transmission paths, the need for flanking measurements and field results for airborne sound transmission has become a major focus. To address this, the National Research Council of Canada (NRC) utilizes a four-room flanking facility that includes both direct and indirect transmission paths. In this study, measured Apparent Sound Transmission (ATL) and the subsequently calculated Apparent Sound Transmission Class (ASTC) results from the four-room flanking facility are compared with field measurements taken in a mass timber building. This study aims to compare the apparent transmission loss between room pairs with a resiliently isolated concrete and CLT panels continuously spanning across a demising wall.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".