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Record W2143104478 · doi:10.1177/0731684409352124

Buckling Analysis of Tapered Composite Beams using a Higher Order Finite Element Formulation

2010· article· en· W2143104478 on OpenAlexaff
Abolghassem Zabihollah, Rajamohan Ganesan

Bibliographic record

VenueJournal of Reinforced Plastics and Composites · 2010
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsFinite element methodMaterials scienceBucklingClassification of discontinuitiesComposite laminatesStructural engineeringStiffnessComposite numberParametric statisticsBeam (structure)Stress (linguistics)Composite materialEngineeringMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

Tapered composite beams are increasingly being used in various engineering applications such as helicopter yoke, robot arms, and turbine blades. In the present work, the buckling analysis of laminated tapered composite beams is conducted using a higher order finite element formulation. In tapered laminates, the material and geometric discontinuities at ply drop-off locations lead to significant discontinuities in stress distributions. Higher order formulation ensures the continuity of the stress distribution through the thickness of a laminate as well as across the element interfaces, which is very important for the analysis of tapered laminates. In addition, higher order finite element formulation requires lesser number of elements in order to achieve reasonably accurate results in buckling analysis. The stiffness coefficients of the tapered laminated beam are determined in the present work based on the stress and strain transformations and the classical laminate theory. A detailed parametric study on various types of tapered composite beams is conducted.

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: none
Teacher disagreement score0.004
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.210
Teacher spread0.205 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Reinforced Plastics and CompositesSame topicComposite Structure Analysis and OptimizationFrench-language works237,207