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Record W2015616255 · doi:10.5539/mas.v8n4p223

Nonlinear Shear Buckling Parametric Finite-Element Analysis of Corrugated Steel Webs

2014· article· en· W2015616255 on OpenAlexvenueno aff
Zhiquan Wen, Wei Wenlong

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBucklingMaterials scienceStructural engineeringShear (geology)Finite element methodComposite materialParametric statisticsNonlinear systemFailure mode and effects analysisShear stressEngineering

Abstract

fetched live from OpenAlex

The corrugated steel web of prestressed concrete box-girder with corrugated steel webs is in pure shear stress state. The shear-resistant capacity of the corrugated steel web is not determined by the shear strength of steel web, but controlled by the shear buckling strength of steel web. The shear buckling mode and ultimate shear capacity of corrugated steel webs are analyzed by nonlinear finite elements method. The corrugated webs are simulated by 8-node structure shell element. The simulation was done for the defect of corrugated steel web with uniform imperfections mode method, and the defects were included in the material nonlinearity and geometric nonlinearity. On this basis, the influences of corrugation configuration, the overall profile dimensions and steel thickness of corrugated webs on ultimate shear buckling load and buckling mode are investigated.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.213 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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