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Record W2163752888 · doi:10.1061/41171(401)53

Reliability Analysis of Masonry Members under Compression

2011· article· en· W2163752888 on OpenAlexaffabout
Seyed Mohammad Kazemi, Mehrdad Mahoutian, Hassan Moosavi, Yasser Korany

Bibliographic record

VenueStructures Congress 2011 · 2011
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMasonryUnreinforced masonry buildingStructural engineeringCompressive strengthMasonry veneerGeotechnical engineeringCompression (physics)Reliability (semiconductor)Materials scienceGeologyEngineeringComposite materialPhysics

Abstract

fetched live from OpenAlex

A structural reliability analysis was performed on concrete masonry under concentric axial compression to examine the reliability levels for masonry buildings designed to the current Canadian masonry standard CSA S304.1-04 (2004). The first order second moment method was used to carry out the analysis. Prism compressive strength for hollow and grouted concrete masonry was used as the model. Over 300 specified masonry compressive strength values were computed using test results available from North American investigations, mostly Canadian. The material and geometry statistical data needed were obtained from several Canadian concrete masonry producers. Based on the findings of this investigation, it is recommended that unreinforced masonry be assigned a material resistance factor (φm) different from reinforced masonry. For masonry members under compression, it is proposed that the current φm be increased from 0.6 to 0.65 for reinforced masonry and decreased from 0.6 to 0.5 for unreinforced masonry. The proposed factors correspond to reliability indices of 3.5 and 3.8 for reinforced and unreinforced masonry, respectively.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
Teacher spread0.207 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

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