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Record W4407924142 · doi:10.1061/jsendh.steng-13972

Vibration Performance of Mass Timber Slab Floors with Glulam Beam Supports

2025· article· en· W4407924142 on OpenAlexaff
Chenyue Guo, Sigong Zhang, Jianhui Zhou

Bibliographic record

VenueJournal of Structural Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsUniversity of AlbertaUniversity of Northern British Columbia
Fundersnot available
KeywordsStructural engineeringSlabBeam (structure)VibrationMaterials scienceEngineeringAcousticsPhysics

Abstract

fetched live from OpenAlex

Mass timber floors are prone to human-induced vibration due to their light weight. Vibration serviceability limit design often governs the maximum allowable span of mass timber floors. The current design methods usually assume the mass timber floors are simply supported on walls, which cannot be directly applied to floors being supported by beams. In this study, the vibration performance of mass timber floors including nail laminated timber, dowel laminated timber, and cross laminated timber floor panels with beam supports was investigated experimentally. Various equations for predicting the system’s fundamental natural frequencies were assessed based on the experimental results. Additionally, a finite element model was proposed and validated using the test results for further vibration analysis. The test results highlighted the substantial influence of support stiffness on the dynamic properties and vibration performance of the floor systems. Specifically, when changing from wall supports to beam supports, the floor’s fundamental natural frequency decreased by up to 40%. This change in support resulted in a shift in vibration performance ratings from acceptable to unacceptable. Dunkerley’s equation and the equation in the draft version of the second generation of Eurocode 5 consistently produced overestimated results for up to 30% when predicting the system’s fundamental natural frequency. In contrast, Kollar’s equation displayed an average error within 5%, with the modification introduced in this research, it demonstrated promising potential for practical application.

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 score0.110
Threshold uncertainty score0.688

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 communication0.0000.000
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 head0.002
GPT teacher head0.176
Teacher spread0.174 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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