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Record W6997130099

Two modeling approaches for periodic rib-stiffened plates typical of floor assemblies

2007· article· en· W6997130099 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2007
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsnot available
Fundersnot available
KeywordsOrthotropic materialJoistVibrationPoint (geometry)Power (physics)Series (stratigraphy)Motion (physics)
DOInot available

Abstract

fetched live from OpenAlex

Floors in lightweight framed construction are periodic orthotropic point connected plate-rib structures formed from orthotropic wood sheathing and a series of joists spaced at a regular interval. These structures are driven into motion by point excitations from people walking, dropping objects, etc. To accurately estimate flanking involving mechanical excitation one must predict the injected power using the mobility of the source and structure, and then estimate the resulting vibration distribution across the periodic floor structure. By examining two prediction approaches - SEA and an analytical solution for an assembly of finite sized plates - this paper shows that the more complex analytic solution gives a much better estimate of the vibration distribution, and is the only method capable of capturing the spatial dependence of the drive-point mobility. The analytic model is then used to identify the parameters of a joist floor that should be considered when designing a floor that has good low frequency impact sound insulation.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.064
GPT teacher head0.280
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 source (direct Gemma or distilled Codex), 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
Published2007
Admission routes1
Has abstractyes

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