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Record W7009430698

Effect of structural changes on acoustic performance of wood frame walls

2012· article· en· W7009430698 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2012
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsStiffnessSoundproofingShear wallBendingShear (geology)Structural load
DOInot available

Abstract

fetched live from OpenAlex

Sometimes in wood frame construction wall assemblies are required that have a higher axial loadbearing capacity than conventional loadbearing wall designs. To increase the axial load bearingcapacity to carry higher vertical loads, i.e. dead load or traffic load of upper building storeys, theframing has to be stronger, which can be achieved by either decreasing the spacing of the studs orby using stronger studs at a wider spacing. These significant structural measures increase the wallstiffness and thus can also affect the airborne sound insulation of the wall assemblies. The effectof wall stiffness on airborne sound insulation was investigated, by analysing bendingwavenumbers measured along the primary axis on the gypsum board leaf of a common staggeredstud wood frame wall and of assemblies with smaller than typical stud spacing (i.e. <400 mm),with multi-stud columns at a wider spacing, and with shear membranes in various configurations.A correlation in the change of bending wavenumber results and the change of airborne soundinsulation was found in frequency ranges where the wall stiffness was influenced by the designchanges. The results are promising and a first step towards a method for the estimation ofairborne sound insulation changes from the mechanical properties of the wall.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2012
Admission routes2
Has abstractyes

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