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Record W2048190899 · doi:10.1098/rspa.2005.1614

Mesoscale bounds in finite elasticity and thermoelasticity of random composites

2006· article· en· W2048190899 on OpenAlexaff
Z. F. Khisaeva, Martin Ostoja‐Starzewski

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2006
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsMcGill University
Fundersnot available
KeywordsThermoelastic dampingRepresentative elementary volumeElasticity (physics)Isochoric processStrain energyFinite element methodLinear elasticityMathematicsMathematical analysisStrain energy density functionElastic energyErgodic theoryMaterials scienceThermalPhysicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Under consideration is the problem of size and response of the Representative Volume Element (RVE) in the setting of finite elasticity of statistically homogeneous and ergodic random microstructures. Through the application of variational principles, a scale dependent hierarchy of strain energy functions (i.e. mesoscale bounds) is derived for the effective strain energy function of the RVE. In order to account for thermoelastic effects, the variational principles are first generalized, and then analogous bounds on the effective thermoelastic response are derived. It is also shown that, in contradiction to results obtained for random linear composites, the hierarchy on the effective strain energy function in nonlinear elasticity cannot be split into volumetric and isochoric terms, while the hierarchy on the effective free energy function cannot be divided into purely mechanical and thermal contributions.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.173
Teacher spread0.169 · 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 designSimulation or modeling
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

Citations28
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of the Royal Society A Mathematical Physical and Engineering SciencesSame topicComposite Material MechanicsFrench-language works237,207