MétaCan
Menu
Back to cohort
Record W4388640740 · doi:10.56830/ijsie06202304

<b>Analyzing the Nonlinear Finite Element Behavior of FRP </b> <b>Composite Electrical Structures in Flexural Loading </b>

2023· article· en· W4388640740 on OpenAlexaff
Hamdy M. Mohamed

Bibliographic record

VenueInternational Journal of Sustainability and Innovation in Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsFibre-reinforced plasticMaterials scienceComposite materialFlexural strengthFinite element methodStiffnessEpoxyFiberGlass fiberComposite numberStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Finite Element Analysis of Flexural Behavior in Full-scale Tapered FRP Pole Structures: Influence of Fiber Orientations, Circumferential Layers, and Carbon Fiber Substitution. In this study, we present a finite element modeling analysis of the nonlinear behavior of laterally loaded full-scale tapered fiber-reinforced polymer (FRP) pole structures. The study explores the impact of various parameters, including fiber orientations in longitudinal and circumferential layers, the number of circumferential layers, and the substitution of glass fiber with carbon fiber in the FRP pole compositions. The FRP poles in question were manufactured using the filament winding technique, with E-glass fiber and epoxy resin as the primary materials. Our analysis results exhibit a significant correlation between the finite element analysis and experimental data, emphasizing the critical role of fiber orientation in determining flexural behavior. The findings underscore the advantages of incorporating circumferential layers and highlight that enhanced strength can be achieved by incorporating both outer and inner circumferential layers alongside longitudinal layers. Moreover, substituting carbon fiber for glass fiber in the FRP poles results in notable improvements, with increased total load capacity and stiffness as the percentage of carbon fibers rises.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.381
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.267
Teacher spread0.256 · 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
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Sustainability and Innovation in EngineeringSame topicMechanical Behavior of CompositesFrench-language works237,207