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Effectiveness of GFRP Sheets for Shear Strengthening of Timber

2006· article· en· W2087550824 on OpenAlexaff
Shaun Hay, Kenton Thiessen, Dagmar Svecova, Baidar Bakht

Bibliographic record

VenueJournal of Composites for Construction · 2006
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFibre-reinforced plasticMaterials scienceDiagonalShear (geology)Structural engineeringFlexural strengthComposite materialStiffnessShear strength (soil)EngineeringGeologyMathematics

Abstract

fetched live from OpenAlex

The objective of this study was to develop a cost-effective shear-strengthening technique for timber stringers that is environmentally friendly and leads to a durable structure. Testing was performed on creosote-treated Douglas fir beams, with dimensions of 100×400×3,650mm , removed from a 40 year old bridge. Two strengthening schemes were investigated; incorporating vertical and diagonal glass fiber-reinforced polymer (GFRP) sheets applied to both shear spans. The diagonal scheme proved effective in increasing the average ultimate load, flexural stiffness, and deformability of the beams. Performance of the members reinforced using the vertical scheme, however, was poor compared to diagonally reinforced beams. The contribution of the diagonal sheets to the shear capacity of the stringers was around 12% at service loads and 40% at ultimate load. In conclusion, this study has shown that diagonal GFRP sheets are more effective than vertical sheets in shear-strengthening timber stringers with horizontal splits at their ends.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.260

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)0.0000.000

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 head0.202
Teacher spread0.196 · 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 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

Citations39
Published2006
Admission routes1
Has abstractyes

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