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Record W2071287299 · doi:10.1098/rsif.2012.0849

An improved failure criterion for biological and engineered staggered composites

2012· article· en· W2071287299 on OpenAlexaff
François Barthelat, Ahmad Khayer Dastjerdi, Reza Rabiei

Bibliographic record

VenueJournal of The Royal Society Interface · 2012
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceComposite materialToughnessUltimate tensile strengthStiffnessShear (geology)Fracture (geology)Fracture toughnessStructural engineeringEngineering

Abstract

fetched live from OpenAlex

High-performance biological materials such as nacre, spider silk or bone have evolved a staggered microstructure consisting of stiff and strong elongated inclusions aligned with the direction of loading. This structure leads to useful combinations of stiffness, strength and toughness, and it is therefore increasingly mimicked in bio-inspired composites. The performance of staggered composites can be tuned; for example, their mechanical properties increase when the overlap between the inclusions is increased. However, larger overlaps may lead to excessive tensile stress and fracture of the inclusions themselves, a highly detrimental failure mode. Fracture of the inclusions has so far only been predicted using highly simplified models, which hinder our ability to properly design and optimize engineered staggered composites. In this work, we develop a new failure criterion that takes into account the complex stress field within the inclusions as well as initial defects. The model leads to an 'optimum criterion' for cases where the shear tractions on the inclusions is uniform, and a 'conservative' criterion for which the tractions are modelled as point forces at the ends of the overlap regions. The criterion can therefore be applied for a wide array of material behaviour at the interface, even if the details of the shear load transfer is not known. The new criterion is validated with experiments on staggered structures made of millimetre-thick alumina tablets, and by comparison with data on nacre. Formulated in a non-dimensional form, our new criterion can be applied on a wide variety of engineered staggered composites at any length scale. It also reveals new design guidelines, for example high aspect ratio inclusions with weak interfaces are preferable over inclusions with low aspect ratio and stronger interfaces. Together with existing models, this new criterion will lead to optimal designs that harness the full potential of bio-inspired staggered composites.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.015
GPT teacher head0.265
Teacher spread0.249 · 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

Citations60
Published2012
Admission routes1
Has abstractyes

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