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Record W3035006966 · doi:10.1139/cjce-2019-0685

Out-of-plane flexural testing and stiffness response of concrete masonry walls with NSM steel reinforcement

2020· article· en· W3035006966 on OpenAlexafffundvenueabout
Adrien Sparling, Dan Palermo, Fariborz Hashemian

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsYork University
FundersCanada Masonry Design Centre
KeywordsMasonryFlexural strengthReinforcementStiffnessStructural engineeringThree point flexural testMaterials scienceFlexural rigidityDeflection (physics)CurvatureGeotechnical engineeringComposite materialGeologyEngineeringMathematics

Abstract

fetched live from OpenAlex

Near-surface mounted (NSM) reinforcement is used to retrofit masonry structures for increased strength and resiliency; however, its application to new masonry construction remains largely unexplored. Four masonry walls measuring 3.2 m tall were constructed from hollow concrete blocks to assess the potential of NSM reinforcement to increase flexural stiffness. Two of the walls were reinforced conventionally, and two were reinforced with NSM bars. Each wall had a total area of steel reinforcement of 600 mm 2 and was loaded under conditions of third-point out-of-plane flexure. All four walls had similar flexural strength, ranging from 24 kNm to 26 kNm; however, the stiffness (determined using direct measurement of curvature, curvature calculated using conditions of equilibrium and compatibility, and the load displacement response) of the NSM reinforced walls was twice that of the walls with conventional reinforcement. The flexural stiffness of the masonry walls was underestimated by current Canadian design standards provisions under low out-of-plane loads.

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 score0.088
Threshold uncertainty score0.889

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 head0.017
GPT teacher head0.196
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 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

Citations8
Published2020
Admission routes4
Has abstractyes

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