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Stability Capacity and Lateral Bracing Requirements of Wood Beam-Columns

2009· article· en· W2023976566 on OpenAlexaff
Xiaobin Song, Frank Lam

Bibliographic record

VenueJournal of Structural Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBracingStructural engineeringStiffnessDeflection (physics)Beam (structure)Structural loadParametric statisticsEccentricity (behavior)BucklingCompression (physics)Finite element methodEngineeringMaterials scienceBraceMathematicsComposite material

Abstract

fetched live from OpenAlex

This paper presents a study on the stability capacity and lateral bracing requirements of wood beam-columns subjected to biaxial eccentric compression loads. Material property tests and wood beam-column tests were conducted to provide input parameters and verification to a finite element method based numerical analysis model. The model provided good predictions of the maximum compression load, midspan lateral deflection and lateral bracing force of the wood beam-columns. A parametric study was conducted for the effect of the lateral bracing stiffness, load eccentricity and initial lateral deflections. The adequacy of the 2% rule-of-thumb, Winter’s and Plaut’s methods was also studied by comparing to the test results of the lateral bracing force. The developed model and its output can be used to improve the design methods of the lateral bracing systems of wood beam-columns.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.197
Teacher spread0.180 · 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 designBench or experimental
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

Citations14
Published2009
Admission routes1
Has abstractyes

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Same venueJournal of Structural EngineeringSame topicWood Treatment and PropertiesFrench-language works237,207