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Record W2898960530 · doi:10.1115/detc2018-86028

Damage Assessment on the Surface and Honeycomb Core of the Aluminum Sandwich Panel Subjected to Low-Velocity Impact

2018· article· en· W2898960530 on OpenAlexaff
Mengqian Sun, Patrick Kendall, Diane Wowk, Il Yong Kim, Christopher Mechefske

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsRoyal Military College of CanadaQueen's University
Fundersnot available
KeywordsSandwich panelMaterials scienceHoneycomb structureIndentationCore (optical fiber)HoneycombSandwich-structured compositeStiffnessComposite materialDeformation (meteorology)AluminiumStructural engineeringComposite numberEngineering

Abstract

fetched live from OpenAlex

Sandwich panels consisting of aluminum face-sheets and honeycomb core are widely used in transportation systems. The composite structure has a high stiffness and strength, but it is susceptible to impacts in service. An experimental investigation of surface deformation and core damage in a honeycomb sandwich panel subjected to three different low-velocity impact energies was undertaken. Surface damage evaluation using 3D laser scanning technology was conducted to assess the surface damage and a comparison was made with two typical indentation profiles which were proposed mathematically in the past. The experimental dent profile shows a good agreement with one of the two analytical dent profiles. The impacted sandwich panel was then cut transversely to study the damage inside the honeycomb core. The number of buckled or collapsed folds under the damaged top face-sheet and the depth of the core damage were utilized as two parameters to quantify the damage of the honeycomb core. It is concluded that the core damage depth and the number of folds is independent of impact energy and is constant within each dent.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.268

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 science0.0000.000
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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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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