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Record W2792856211 · doi:10.5539/mas.v12n3p117

Sandwich Panel Behavior for Core Loading Beyond the Yield Limit

2018· article· en· W2792856211 on OpenAlexvenueno aff
Salih N. Akour, Hussein Maaitah

Bibliographic record

VenueModern Applied Science · 2018
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsnot available
Fundersnot available
KeywordsSandwich panelCore (optical fiber)StiffnessYield (engineering)Finite element methodMaterials scienceSandwich-structured compositeStructural engineeringLimit (mathematics)Point (geometry)Boundary value problemComposite materialEngineeringMathematicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

The effect of loading core material beyond its yield limit on sandwich panel behavior is investigated. Different core materials of different stiffness are studied. The panel modeled using a finite element analysis package. Simply supported boundary conditions are applied on all sides of the panel. The effect of core stiffness is investigated parametrically by utilizing univariate search optimization technique. The load has been increased in quasi–static steps till face sheets reach the yield point. The model has been validated analytically and experimentally for selected cases. The finite element model results show very good agreement with the analytical and the experimental results investigation. It is proved in this study that the load carrying capacity of the panel increases as the core material goes beyond the yield point. Load transmitted to the face sheets increases as the core stiffness gets softer. As core material is getting stiffer face sheets of sandwich panel yield before the core.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.464
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.040
GPT teacher head0.242
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 teacher head, 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

Citations2
Published2018
Admission routes1
Has abstractyes

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