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Record W2891323392 · doi:10.1177/1081286518797993

Coated inhomogeneities of arbitrary shape with internal uniform hydrostatic stress resultants in isotropic laminated plates

2018· article· en· W2891323392 on OpenAlexafffund
Xu Wang, Liang Chen, Peter Schiavone

Bibliographic record

VenueMathematics and Mechanics of Solids · 2018
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceStress resultantsIsotropyCoatingHydrostatic equilibriumComposite materialStress (linguistics)BendingBending momentBending of platesHydrostatic stressCylinder stressGeometryMechanicsMathematicsStructural engineeringPhysicsOpticsFinite element method

Abstract

fetched live from OpenAlex

We study the internal stress resultants inside an elastic inhomogeneity of arbitrary shape embedded in an infinite Kirchhoff plate (matrix) via an intermediate coating. Each material phase is considered an isotropic laminated plate and the surrounding matrix is subjected to uniform remote membrane stress resultants and bending moments. We find that internal uniform hydrostatic stress resultants within the inhomogeneity can be achieved when (i) the mapping function characterizing the shape of the inhomogeneity is identified and specialized accordingly; (ii) the relative coating thickness should satisfy a higher-order algebraic equation; (iii) several restrictions on the remote loading should be satisfied for given material and geometric parameters of the composite plate. When all these conditions are met, the hoop membrane stress resultant and hoop bending moment on the coating side are uniform along the entire inhomogeneity–coating interface.

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 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 score0.460
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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.

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
Published2018
Admission routes2
Has abstractyes

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