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Record W2053477294 · doi:10.2514/2.991

Higher-Order Finite Element for Sandwich Plates

2000· article· en· W2053477294 on OpenAlexaff
S. Oskooei, J. S. Hansen

Bibliographic record

VenueAIAA Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinite element methodStructural engineeringOrder (exchange)Materials scienceMathematicsGeometryEngineering

Abstract

fetched live from OpenAlex

A finite element model for the analysis of sandwich plates with laminated composites facesheets is developed. In the model, the facesheets are represented as Reissner-Mindlin plates and the core is modeled as a three-dimensional continuum in which the through-thickness representation of the displacement fields is of a mixed form. That is, the u and v deflections are cubic functions of z, whereas w is a quadratic function of z. This representation allows accurate modeling of a wide range of core types (honeycomb and foam) and in particular core materials that have low in-plane stiffness compared to the transverse stiffness. Also, these through-thickness trial functions allow an accurate representation of transverse shear and normal stresses. The presented model provides a powerful general tool for the analysis of sandwich plates; transverse normal and shear stresses can be determined explicitly at the core/facesheet interface. Also, because of the core model adopted, good accuracy is obtained when large differences in transverse vs in-plane core stiffness is present, as well as for cases in which the core stiffness changes rapidly in the plane of the plate. The capability of the model is illustrated with several examples.

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)0.001
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.005
GPT teacher head0.206
Teacher spread0.201 · 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

Citations51
Published2000
Admission routes1
Has abstractyes

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Same venueAIAA JournalSame topicComposite Structure Analysis and OptimizationFrench-language works237,207