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Record W3208871548 · doi:10.32920/ryerson.14644572.v1

Behaviour of composite framed shear wall system

2021· preprint· en· W3208871548 on OpenAlexaff
Muhammad Akram

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsStructural engineeringShear wallComposite numberMaterials scienceCrackingShear (geology)BucklingInfillStiffnessJoint (building)FastenerShear strength (soil)Composite materialEngineeringGeology

Abstract

fetched live from OpenAlex

This research investigated the behaviour of a novel form of composite framed shear wall system (CFSWS) under lateral loading. The CFSWS consisted of a composite wall (made of two skins of profiled steel sheeting and an infill of concrete) connected to pinned steel or fixed concrete filled steel tube (CFST) frame. The experimental investigations on one and two-storey four CFSWS models of 1/6th scale provided information on shear load-deformation response, shear strength/stiffness, energy absorbing capacity, stress-strain characteristics and failure modes. The failure of CFSWS was associated with buckling of steel sheets and development of diagonal concrete core cracking as well as the wall-frame fastener and CFST frame joint failure. Overall, the failure was governed by wall failure rather than frame. Analytical models for the shear strength of CFSWS were developed and found to be in close agreement with experiments. This research confirmed the viability of using novel CFSWS in practical construction.

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)0.000
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.213
Teacher spread0.203 · 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
Published2021
Admission routes1
Has abstractyes

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