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Record W2085572242 · doi:10.1260/1369-4332.14.4.659

Floor Vibration in Lightweight Cold-Formed Steel Framing

2011· article· en· W2085572242 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Structural Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsServiceability (structure)Framing (construction)Structural engineeringVibrationStiffnessCold-formed steelEngineeringFinite element methodAcoustics

Abstract

fetched live from OpenAlex

Floor vibration due to walking as a serviceability concern has not been well addressed in design and construction of lightweight floors. The high strength and stiffness of steel provide the advantage of achieving longer floor spans. However, floors with longer span and lighter weight are likely to be susceptible to annoying vibrations induced by normal human activity such as walking. Designing a lightweight floor to control these annoying vibrations can be difficult due to lack of appropriate design guidelines. Presented in this paper is a multi-phase study on the vibration performance of cold-formed steel floors performed at the University of Waterloo. Full-scale floor systems with different framing details were constructed and tested in both laboratory and in situ conditions. The floor framing details that enhance the floor performance against vibrations are discussed. The results of the tests show that cold-formed steel floor systems with appropriate design and construction details can perform well against floor vibration due to human walking.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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