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Record W2806599076 · doi:10.5267/j.esm.2018.3.005

Edgewise and flatwise compressive behaviour of foam-filled sandwich panels with 3-D high density polyethylene skins

2018· article· en· W2806599076 on OpenAlexvenueno aff
P. Sharafi, Saeed Nemati, Bijan Samali, Akbari Mousavi, Shahab Khakpour, Yahya Aliabadizadeh

Bibliographic record

VenueEngineering Solid Mechanics · 2018
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComposite materialCompressive strengthPolyethyleneStructural engineeringSandwich-structured compositeComposite numberEngineering

Abstract

fetched live from OpenAlex

In this paper, the edgewise and flatwise compressive behaviour of an innovative sandwich panel, mainly developed for quick assembly of post-disaster housing as well as load bearing panels for pre-fabricated modular construction and semi-permanent buildings, is investigated experimentally and by finite element modelling. The panel is composed of two 3-D highdensity polyethylene (HDPE) sheets as the skins, filled with high-density Polyurethane (PU) foam as the core. HDPE sheets manufactured with a studded surface considerably enhance the stress distribution and buckling performance of the sandwich panel. Material characterisation tests and flatwise compression and edgewise compression experiments were performed in accordance with ASTM standards to evaluate the compressive strength and the load-carrying behaviour of the sandwich panels. A finite element analysis and validation were also conducted to model the compressive behaviour of sandwich structures. Results demonstrate that the developed sandwich panel exhibits very good compressive performance.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
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 head0.003
GPT teacher head0.181
Teacher spread0.177 · 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 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

Citations16
Published2018
Admission routes1
Has abstractyes

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