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Record W4414247639 · doi:10.1080/15376494.2025.2560475

Compressive properties of multi-hierarchical hybrid reentrant honeycombs

2025· article· en· W4414247639 on OpenAlexaff
Mingming Su, Ao Zhang

Bibliographic record

VenueMechanics of Advanced Materials and Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsMétis National Council
FundersNatural Science Foundation of Hebei Province
KeywordsReentrancyCompressive strengthHoneycombCompression (physics)Composite number

Abstract

fetched live from OpenAlex

In this study, the two- and three-hierarchical hybrid reentrant honeycombs were designed with reentrant hexagon as main unit, ellipse and missing-rib as support units. The effects of support units and concave Angle on compressive characteristics were explored. Through the experiment and simulation analysis, the compressive curves of the two-hierarchical honeycombs had a long plateau stage (close to 0.3 strain) in the early deformation to fully buffer. The ellipse and missing-rib made the deformation more stable, and their energy absorption was nearly twice and 1.8 times that of 2RH, respectively. The concave Angles θ and α of one- and two-hierarchies affected the later segmentation of the compressive curves. The three-hierarchical honeycombs showed that the upper layer deformed first and the lower layer deformed later. According to the Poisson’s rate-strain curves, the deformation of the lower layer of the three-hierarchical honeycombs was more severe than that of the upper layer when α = 70°, while the deformation was opposite when α = 60° and 50°. This study offered valuable insights into multi-hierarchical hybrid structures with auxetic behavior.

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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