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Record W2512247418

SCALE-MODEL INVESTIGATION OF THE EFFECT AND OPTIMAL DESIGN OF SOUND ABSORBERS IN AN OPEN-PLAN OFFICE

2016· article· en· W2512247418 on OpenAlexvenueaboutno aff
Amin Mahmud, Murray Hodgson

Bibliographic record

VenueCanadian acoustics · 2016
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsCeiling (cloud)BaffleScale modelAcousticsReverberationAbsorption (acoustics)Open planScale (ratio)Sound (geography)EngineeringStructural engineeringPhysicsMechanical engineeringAerospace engineering
DOInot available

Abstract

fetched live from OpenAlex

The UBC Vancouver AERL building fourth-floor open-plan student area contains TECTUM sound-absorptive baffles located flat against, and suspended from, the ceiling. Is this the optimal configuration or would they, for example, be more effective if located in a different configuration? This paper discusses tests performed in a 1:8-scale open-plan model with 18 workstations, using a suitable 1:8-scale-model sound-absorbing material (6-mm-thick felt), to investigate the sound absorption provided by acoustical treatments such as baffles in AERL and find the optimal configuration. Both the reverberation time (T_20 in s) and sound level decrease per doubling of distance (DL2 in dB/dd) were tested for 15 different absorber configurations (suspended, ceiling-mounted and sidewall absorbers and their various combinations), including the current configuration. The optimal absorber configuration ? absorber covering the whole ceiling and, the second best, a combination of all types of absorber ? was the same for both T_20 and DL2, and performed much better than the current configuration of the AERL space area.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.331

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 head0.028
GPT teacher head0.244
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations0
Published2016
Admission routes2
Has abstractyes

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