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Record W4313557218 · doi:10.1520/stp164020210117

A Look to the Past: Reevaluation of the Performance of Tall Slender Concrete Masonry Walls

2022· book-chapter· en· W4313557218 on OpenAlexaboutno aff
Alan Alonso, Rafael Gonzalez, Mahmoud Elsayed, Bennett Banting, Monica Guzman, Douglas Tomlinson, Carlos Cruz-Noguez

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMasonryStructural engineeringEngineeringGeologyForensic engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Slender masonry walls (SMWs) with a slenderness ratio (kh/t) over 30 have stringent design requirements in North American codes (TMS 402/602-16; CSA S304-14). As a result, in some design scenarios masonry struggles to be a competitive option compared to other systems. The limits and requirements for tall walls are largely based on a comprehensive investigation conducted by the American Concrete Institute and the Structural Engineers Association of Southern California 41 years ago. Since then, understanding of these slender elements has advanced, and the tools for a more refined analysis have become easily available to practicing engineers. Furthermore, recent studies highlight the need to reevaluate the performance of these walls and the requirements in the design standards. In this study, a full-scale SMW built using concrete masonry units subjected to eccentric axial and cyclic out-of-plane loads was tested, the first of a series of tests conducted at the University of Alberta to reevaluate the strength and behavior of tall concrete masonry walls; the test aimed to generate a rational design procedure for modern SMWs.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.741
Threshold uncertainty score0.990

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)0.0100.000

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 head0.012
GPT teacher head0.195
Teacher spread0.183 · 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.

Study designSimulation or modeling
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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