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Record W2018046485 · doi:10.1139/l10-096

Analysis and design of steel plate walls: experimental evaluation

2010· article· en· W2018046485 on OpenAlexaffvenue
Mehdi Kharrazi, Carlos E. Ventura, Helmut G. L. Prion

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsIntecsea (Canada)University of British Columbia
Fundersnot available
KeywordsStructural engineeringInfillStiffnessWeldingYield (engineering)Materials scienceColumn (typography)Beam (structure)EngineeringComposite material

Abstract

fetched live from OpenAlex

In this paper, the effectiveness of the Modified Plate–Frame Interaction (M-PFI) model is evaluated by comparing its outcomes against those from experimental results obtained from a number of steel plate walls (SPWs) tested at different universities. As a result of the comparison, the M-PFI model was found to provide satisfactory predictions for SPW specimens constructed with steel plates welded to column and beam members. The M-PFI model was able to predict the initial stiffness, as well as to evaluate whether the boundary members of the SPW have sufficient capacity to allow for the infill plate to yield entirely. However, the model was found to underestimate the ultimate capacity of the SPW system mainly because, among other reasons, the material model used for its underlying theory is the elastic – perfectly plastic material model.

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)0.002
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.215
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 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

Citations5
Published2010
Admission routes2
Has abstractyes

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