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Record W4402544010 · doi:10.1093/qjmam/hbae010

The steady-state response of a three-phase elliptical inhomogeneity with interface slip and diffusion under an edge dislocation in the matrix

2024· article· en· W4402544010 on OpenAlexaff
Xu Wang, Peter Schiavone

Bibliographic record

VenueThe Quarterly Journal of Mechanics and Applied Mathematics · 2024
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDislocationSlip (aerodynamics)Materials scienceEnhanced Data Rates for GSM EvolutionSteady state (chemistry)DiffusionPhase (matter)MechanicsCondensed matter physicsGeometryPhysicsMathematicsComposite materialThermodynamicsChemistryComputer science

Abstract

fetched live from OpenAlex

Abstract We study the steady-state response of a three-phase elliptical inhomogeneity in which the internal elliptical elastic inhomogeneity is bonded to the surrounding infinite matrix through an interphase layer with two confocal elliptical interfaces permitting simultaneous interface slip and diffusion. The matrix is subjected to an edge dislocation at an arbitrary position and uniform remote in-plane stresses. An analytical solution to the steady-state problem is derived using Muskhelishvili’s complex variable formulation. The effect of the edge dislocation and remote loading on the elastic fields in the inhomogeneity and the interphase layer is exhibited through a single loading parameter. More specifically, when divided by this loading parameter, the expressions for the stresses and strains in the inhomogeneity and the interphase layer are uninfluenced by the specific loading applied in the matrix. After excluding a particular common factor, the stresses and strains in the inhomogeneity and the interphase layer are also unaffected by the mismatch in shear moduli between the interphase layer and the matrix.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.012
GPT teacher head0.258
Teacher spread0.245 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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