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Record W7038074995

Floor excitation with the heavy soft impact source

2011· article· en· W7038074995 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2011
Typearticle
Languageen
FieldEngineering
TopicStonefly species taxonomy and ecology
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDeflection (physics)ModalExcitationBall (mathematics)Finite element methodModal analysisNumerical analysis
DOInot available

Abstract

fetched live from OpenAlex

Low frequency impact sound is one of the most common reasons for complaints by buildingoccupants. Therefore, some countries, Japan and Korea, have introduced heavy soft impactsources into their standards ? the ?tire? and the ?rubber ball? - that effectively excite lowfrequency sound. Both are dropped from a specified height on the floor under test. Although theball was introduced more recently, it seems to be more accepted by engineers in the field becauseof the ease of handling. In previous studies, to better understand the floor excitation by the ball, asimple analytical model that does not account for modal ball deflection was applied to predict itsblocked force. Good agreement between prediction and measurement was found in the lowfrequency range, however, the analytical model grossly underestimated the blocked force in themid and high frequency range. In this paper the finite element method is applied to predict themodal deformation of the ball during impact on the floor. The results of this numerical study helpsto better understand discrepancies found in earlier publications between the analytic ball modeland measurement. Conclusions for the improvement of the analytical model are finally drawn.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.999

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)0.0020.000

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 head0.016
GPT teacher head0.192
Teacher spread0.176 · 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.

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

Citations0
Published2011
Admission routes2
Has abstractyes

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