MétaCan
Menu
Back to cohort
Record W1991259228 · doi:10.1139/l03-048

Analysis of load in ties in masonry veneer walls

2003· article· en· W1991259228 on OpenAlexfundvenueno aff
Junyi Yi, David Laird, Bill McEwen, Nigel G. Shrive

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
FundersCanada Masonry Design Centre
KeywordsMasonry veneerMasonryVeneerStructural engineeringCrackingFinite element methodEngineeringJoint (building)MortarGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Masonry is frequently used as a veneer, tied to a backup structural system. In many cases, the structural system is steel studding. Very little research has been conducted to examine the effect of staggering the ties between the veneer and the backup on the load distributions in the ties and studs. This paper describes three-dimensional (3-D) finite element models developed for masonry veneer walls (brick veneer – steel stud) subjected to wind load. Various tie arrangements were analyzed. Shell elements were used to model the brick veneer, and beam elements were used to model the steel studs and ties. Cracking was introduced in a horizontal mortar joint through the use of gap elements (discrete cracking method). The loads in the ties for various tie arrangements were examined. It appears that staggering the ties does not overload them when a full row of ties is provided at the top or at both the top and the bottom. The load distribution in the ties in a staggered arrangement is close to that in the full-tie arrangement.Key words: masonry veneer walls, 3-D, finite element models, brick veneer, steel studs, ties.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.169
Teacher spread0.163 · 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

Citations7
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicMasonry and Concrete Structural AnalysisFrench-language works237,207