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Behavior and Modeling of Glulam Beams with Bolted Connections Subjected to Shock Tube–Simulated Blast Loads

2020· article· en· W3095935168 on OpenAlexaffabout
Christian Viau, Ghasan Doudak

Bibliographic record

VenueJournal of Structural Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsUniversity of OttawaRoyal Military College of Canada
Fundersnot available
KeywordsStructural engineeringBrittlenessFailure mode and effects analysisDissipationDuctility (Earth science)EngineeringBendingMaterials scienceComposite material

Abstract

fetched live from OpenAlex

An experimental program investigating the behavior of glued laminated timber (glulam) assemblies with various bolted connections subjected to simulated blast loading was undertaken. A total of 14 full-scale tests on 137×267-mm glulam members with idealized and realistic boundary conditions were carried out using a shock tube apparatus capable of simulating the effects of far-field blast explosions. Full-scale glulam specimens with bolted connections designed to yield in bolt bending performed better than those that were overdesigned. Proper detailing of the bolt group geometry was found to be sufficient to achieve the desired failure sequence. Reinforcement with self-tapping screws changed the failure mode from that of splitting to a combination of bolt yielding and wood crushing and provided additional ductility in the assembly. A two-degree-of-freedom blast analysis was found to adequately capture the system response with reasonable accuracy. An investigation of the current Canadian blast design provisions showed that the design approach does not allow for energy dissipation in the assembly. An approach is proposed that requires more stringent provisions for the design of brittle failure modes in connections and ensures that ultimate failure will occur in load-bearing timber elements.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.210
Teacher spread0.201 · 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 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

Citations30
Published2020
Admission routes2
Has abstractyes

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