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Record W4389056735 · doi:10.3390/buildings13122943

Effects of Building Height on the Sound Transmission in Cross-Laminated Timber Buildings—Vibration Reduction Index

2023· article· en· W4389056735 on OpenAlexaff
Erik Nilsson, Sylvain Ménard, Delphine Bard, Klas Hagberg

Bibliographic record

VenueBuildings · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsSoundproofingVibrationReduction (mathematics)Structural engineeringFlanking maneuverTransmission (telecommunications)Range (aeronautics)Sound transmission classIndex (typography)Materials scienceAcousticsEngineeringComposite materialElectrical engineeringPhysicsComputer scienceMathematicsGeometry

Abstract

fetched live from OpenAlex

High-rise wooden buildings are increasing in popularity, and they typically include cross-laminated timber in the structure. Taller buildings result in higher loads on the junctions lower down in the building, which are suggested in the literature to negatively affect the sound insulation. This study involved measurement of the vibration reduction index in four different CLT buildings, varying in height and junction details. A total of 12 junctions were measured at both high and low levels in the buildings. Among these, 10 junctions had resilient interlayers with different stiffnesses dependent on the designed quasi-permanent load, while 2 junctions lacked resilient interlayers. The results indicated that the vibration reduction index decreases lower down in the building mainly for the Wall–Wall path. The findings were consistent for all measured junctions above 400 Hz for the Wall–Wall path and for the majority of the measurements of the remaining frequency range, 400 Hz and below. The observed difference in the vibration reduction index could significantly impact the final result if a high-rise building has several flanking paths that affect the sound insulation between two apartments, and this needs to be considered during the design phase. Similar effects were shown for buildings both with and without resilient interlayers in the junctions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.236
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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