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Record W2145504466 · doi:10.1139/l02-104

Design rules for hollow concrete masonry walls subjected to concentrated loads

2003· article· en· W2145504466 on OpenAlexfundvenueno aff
Junyi Yi, Nigel G. Shrive

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMasonryStructural engineeringGeotechnical engineeringEccentricity (behavior)Masonry veneerMaterials scienceGeologyBearing capacityStructural loadLoad bearingEngineering

Abstract

fetched live from OpenAlex

Design rules are proposed for assessing the bearing strengths of hollow concrete masonry walls subjected to in-plane concentrated loads. These are derived from numerical and experimental studies of this problem. Two possible zones of failure are considered: the solid–grouted masonry directly beneath the concentrated loads, and the hollow masonry beneath the grouted portion. The important factors influencing the bearing strength are taken into account: loading eccentricity across the wall width, effective loading area, loading plate length, and loading location along the wall. An angle of 22° or slope (vertical to horizontal) of 2.5:1 is chosen for a safe estimate of the dispersion of concentrated load through the solid–grouted masonry. For partial grouting patterns, at least two courses downward should be grouted to a length compatible with the loading plate. When compared with the available numerical and experimental results, conservative estimates of ultimate strength are obtained in all cases.Key words: design rules, hollow concrete masonry wall, in-plane concentrated load, out-of-plane eccentricities, loading plate length, loading locations, dispersion angle.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.181
Teacher spread0.171 · 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 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

Citations3
Published2003
Admission routes2
Has abstractyes

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