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Record W4297007022 · doi:10.1177/10996362221127968

Design analysis and testing of flat sandwich panels under bird strike

2022· article· en· W4297007022 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Sandwich Structures & Materials · 2022
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsStructural engineeringDeflection (physics)Sandwich-structured compositeCore (optical fiber)Materials scienceNumerical analysisStrain energyComposite materialFinite element methodEngineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

A non-linear energy-based analytical approach to design flat sandwich panels resistant to bird strike is presented. The approach is then complemented by numerical simulation in Abaqus using smooth particle hydrodynamics to model the bird and a non-linear stress-strain model for the core material. Flat sandwich panels were designed to deform and just fail when the maximum deflections are reached for given strike energies. The panels designed with this approach were tested using gelatin birds and two different material combinations with non-toughened and toughened facesheet and core materials. The analytical and numerical approaches were found to be conservative as they predicted failure onset for the bird energies selected while the tests showed no damage. The maximum deflection and maximum strains at different locations of the panels were well predicted by the numerical analysis, but the predictions departed significantly from the tests after the first peak was reached.

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.

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 score0.380
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.248
Teacher spread0.227 · 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