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Deflection criteria for controlling timber floor vibrations: A 200-year evolution

2024· article· en· W4405664298 on OpenAlexafffund
Sigong Zhang, Jianhui Zhou, Ying Hei Chui

Bibliographic record

VenueEngineering Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of AlbertaUniversity of Northern British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaRoyal Society
KeywordsDeflection (physics)VibrationStructural engineeringEngineeringArchitectural engineeringCivil engineeringForensic engineeringGeologyPhysicsAcoustics

Abstract

fetched live from OpenAlex

Timber floor vibrations have long been a significant challenge in design and research, growing in importance with advancements in engineered wood products and the increasing use of mass timber panels. Since the publication of Thomas Tredgold's Elementary Principles of Carpentry in 1820, deflection limits have been essential in controlling excessive vibrations in timber floors, a practice that has evolved over 200 years. Despite updates to align with modern construction and timber engineering innovations, these criteria are often deemed insufficient for mass timber floor systems, underscoring the need for more rational analyses. This review examines the evolution of deflection criteria for timber floor vibrations and identify critical technical aspects for future design criteria, especially for mass timber floors. It highlights two distinct paradigms for floor vibrations: acceptability-based and perception-based. The deflection criteria, derived from acceptability-based studies, integrate three key factors: vibration source, transmission path, and occupant response (receiver), offering a practical and effective solution for controlling timber floor vibrations, despite being essentially empirical. In the future, a reliability-based approach is urgently needed to handle the significant uncertainties involved. Additionally, the human side of floor vibration serviceability equation has been least studied, emphasising the importance of recognising the variability and subjectivity of human responses. • This review traces the 200-year evolution of deflection criteria for controlling timber floor vibrations. • Advancements and shifts in deflection criteria are highlighted, providing insights into their effectiveness and limitations. • A detailed comparison of acceptability-based and perception-based paradigms was conducted. • Two problem-solving strategies for floor vibration were summarised.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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 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

Citations9
Published2024
Admission routes2
Has abstractyes

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