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Record W1972028169 · doi:10.1177/0021998305055196

Closed-form Solutions for the Overall Coefficient of Thermal Expansion of n-phase Fiber Composites with Arbitrary Fiber Orientation

2006· article· en· W1972028169 on OpenAlexaff
Ernest T. Y. Ng, Geoffrey Michael Wood, Afzal Suleman

Bibliographic record

VenueJournal of Composite Materials · 2006
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMaterials scienceThermal expansionComposite materialFiberThermoelastic dampingVolume fractionComposite numberEpoxyPhase (matter)Fiber-reinforced compositeOrientation (vector space)Aspect ratio (aeronautics)GraphiteExpansion ratioThermalGeometryMathematics

Abstract

fetched live from OpenAlex

The coefficient of thermal expansion (CTE) is an important physical property of fiber composites. In the past, researchers have provided closed-form expressions for CTE for 2D and 3D random fiber composite structures. In this study, closed-form solutions for the overall CTE of n-phase fiber composites with arbitrary fiber orientation angles are derived based on the volume-weighted averaging equation. The overall unidirectional (fully aligned fibers) thermoelastic properties are developed using the transformation field analysis (TFA) method. In addition, the mechanical concentration factors are estimated using the Eshelby-Mori-Tanaka (EMT) theory. The proposed model allows for varying the fiber volume fraction, aspect ratio, geometry of the fibers, and fiber orientations while designing to meet different criteria. The results obtained using the derived equations are compared and validated with the results published in the literature. Also, a numerical study for an epoxy/graphite composite structure with a range of orientation angles is presented.

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 score0.072
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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

Citations7
Published2006
Admission routes1
Has abstractyes

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