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Record W4401542219 · doi:10.1177/09544062261430975

Polymer Micro-Lattice Buffer Structure Free Impact Absorption

2024· preprint· en· W4401542219 on OpenAlexafffund
Louis Catar, Ilyass Tabiai, David St-Onge

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · 2024
Typepreprint
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsÉcole de Technologie Supérieure
FundersFonds de recherche du Québec – Nature et technologies
KeywordsLattice (music)PolymerBuffer (optical fiber)Materials scienceComposite materialComputer sciencePhysicsTelecommunicationsAcoustics

Abstract

fetched live from OpenAlex

Advances in miniaturized electronics, perception modules, and flight controllers have expanded the use of uncrewed aerial systems (UAS) to indoor applications such as warehouse management, inspection, and subterranean exploration. Yet, no safety standards currently address the risks of lightweight aerial vehicles operating near humans. This study investigates ultra-light micro-lattice structures as protective elements to enhance crashworthiness without significantly affecting flight endurance. Patch samples with Face-Centered Cubic (FCC), Diamond (D), Kelvin (K), and Gyroid (GY) patterns were fabricated at an effective density of 65 kg/m 3 and tested under compression and impact loading. Results show that Diamond and Kelvin lattices distribute loads more efficiently, achieving specific energy absorption values above 1000 J/kg, while impact tests reveal that flexible patches dissipate energy more effectively and maintain integrity under dynamic loading compared to rigid designs.

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 score0.002
Threshold uncertainty score0.008

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)0.0020.001

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering ScienceSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207