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Quasi-static compressive behaviour of Bézier function-based body-centred cubic lattice sandwich structures

2025· article· W4415285575 on OpenAlexaff
He Zhang, Furong Liu

Bibliographic record

VenueJournal of Physics Conference Series · 2025
Typearticle
Language
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsLattice (music)Deformation (meteorology)Crystal structureDeformation mechanismStiffnessCore (optical fiber)Ductility (Earth science)Bending

Abstract

fetched live from OpenAlex

Abstract To improve the energy absorption performance of single-layer body-centred cubic (BCC) lattice sandwich structures, this study proposes a design method for a Bézier function-defined body-centred cubic lattice core (BCCB). By conducting screening, the unit cell with excellent energy-absorbing performance is obtained. The mechanical response and energy-absorbing mechanism under quasi-static compression are analysed in conjunction with finite-element simulation, and the effect of rod diameter is also explored. It has been demonstrated that the single-layer BCCB lattice sandwich structure exhibits a layered deformation mechanism under compressive loading, enhancing the energy-absorbing capacity through the alternating formation of plastic hinges in the upper and lower parts of the unit cell, the bending deformation of rods, and the interaction between the core and panels. The increase in diameter enhances both the initial stiffness and energy absorption of the structure; however, its effect on specific energy absorption (SEA) remains limited due to the material’s ductility constraints. Additionally, for the single-layer BCCB lattice sandwich structure with SEA in this study, the deformation mode is minimally affected by changes in diameter.

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 categoriesMeta-epidemiology (narrow)
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 score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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.

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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