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Thermomechanical behaviour of glued-in steel rods in glulam timber under steady-state and transient temperature conditions

2025· article· en· W4414306853 on OpenAlexafffund
Jacob Yager, Bronwyn Chorlton, Joshua E. Woods

Bibliographic record

VenueInternational Journal of Adhesion and Adhesives · 2025
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of CalgaryQueen's UniversityHudbay Minerals (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEmbedmentEpoxyRodCuring (chemistry)AdhesiveGlass transitionEpoxy adhesiveThermal

Abstract

fetched live from OpenAlex

The strength of glued-in rod connections under mechanical loading has been extensively studied in the literature. However, there have been comparatively few studies examining their performance under combined mechanical and thermal loading, something that is of concern because of the low glass transition temperature (∼40-80 °C) of adhesives used in these connection types. This paper discusses experimental results from a series of glued-in rod connections tested under thermomechanical loading, including both steady-state and transient temperature tests. The influence of embedment length, epoxy class (one epoxy intended for use in ambient conditions, and one epoxy intended for high temperature applications), epoxy curing method, and encapsulation of the timber on the maximum rod temperature at failure and the failure time were investigated. Furthermore, the residual strength of the connections after cooling was also investigated. Results of the study demonstrate that embedment length is the most influential factor on the thermomechanical performance of glued-in rod connection and that extending the embedment length beyond what is required to yield the rod can result in further improvements in thermomechanical performance. Results also showed that use of a higher glass transition temperature, achieved through specific curing protocols or using specialized high-temperature adhesives increased the maximum rod temperature at failure from 60 °C to 120 °C. The use of encapsulation was found to increase the failure time by up to 1.3 times when compared to the control.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.291

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 head0.009
GPT teacher head0.254
Teacher spread0.245 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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