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Record W2047717408 · doi:10.1177/1099636212460540

Finite element buckling analysis of laminated composite sandwich panels with transversely flexible core carrying attached elastic strip

2012· article· en· W2047717408 on OpenAlexaff
Karamat Malekzadeh Fard, Alireza Sayyidmousavi, Zouheir Fawaz, Habiba Bougherara

Bibliographic record

VenueJournal of Sandwich Structures & Materials · 2012
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFinite element methodBucklingStructural engineeringSandwich-structured compositeStiffnessCore (optical fiber)Boundary value problemShell (structure)Materials scienceDisplacement (psychology)Composite materialEngineeringMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

In this article, a three-dimensional finite element model is proposed to study the effect of distributed attached mass with thickness and stiffness on the buckling instability of sandwich panels with transversely flexible cores. Unlike the previous works in the literature which have made use of unified displacement theories, the present model uses different types of finite elements to model the core and the face sheets. It utilizes shell elements for the face sheets and three-dimensional solid elements for the core which enables the model to account for the transverse flexibility of the structure. The motions of the face sheets and the core as well as the attached mass are related through defining constraint equations between the nodes of their respective finite elements based on the concept of master and slave nodes which is incorporated into the finite element analysis program ANSYS through a user-defined subroutine. The validated finite element model is then used to study the effects of size, thickness, material property, aspect ratio, and the position of the attached mass on the buckling load of a sandwich panel under different combinations of boundary conditions. The results presented in this study have hitherto not been reported in the literature.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.246
Teacher spread0.232 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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