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Record W2974650323 · doi:10.1115/1.4044896

Thermal Expansion Induced Neutrality of a Circular and an Annular Elastic Inhomogeneity

2019· article· en· W2974650323 on OpenAlexafffund
Kun Song, Haopeng Song, Peter Schiavone, Cun‐Fa Gao

Bibliographic record

VenueJournal of Applied Mechanics · 2019
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Alberta
FundersGraduate Research and Innovation Projects of Jiangsu ProvinceChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMaterials scienceStress fieldThermal expansionStress (linguistics)Field (mathematics)Tension (geology)Body forceThermalMechanicsMatrix (chemical analysis)Composite materialPhysicsUltimate tensile strengthFinite element methodMathematicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract An elastic inhomogeneity is termed neutral if its introduction does not disturb the original stress field in the initially uncut elastic body. Neutrality in this sense is often achieved by appropriate design criteria such as a careful choice of the shape of the inhomogeneity and the properties of the interfacial layer between the inhomogeneity and its surrounding matrix. Unfortunately, mismatched stress and strain fields in the resulting composite structure make it difficult to simultaneously control both the shape of the inhomogeneity and its interfacial properties to achieve the desired neutrality property. We assert that the associated temperature field can be used to adjust the stress and strain fields within the inhomogeneity via thermal expansion, thus allowing us to control the properties of the interfacial layer for a given shape of inhomogeneity. Our theoretical results show that the design of a neutral circular or annular elastic inhomogeneity requires an accompanying internal uniform temperature field when the elastic body is in equi-biaxial tension and an internal temperature field which is quadratic if the body is subjected to uniaxial tension or shear force. More importantly, in contrast to the well-established result in the literature for a purely elastic inhomogeneity, under certain conditions, a neutral elastic inhomogeneity can be designed via thermal expansion despite the assumption of a perfectly bonded interface between the inhomogeneity and the surrounding 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)0.000
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 score0.042
Threshold uncertainty score0.641

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 head0.010
GPT teacher head0.211
Teacher spread0.202 · 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

Citations1
Published2019
Admission routes2
Has abstractyes

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