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Record W2619500366 · doi:10.11159/icmie17.107

Failure Prediction of Composite Laminates under Out-of-Plane Loading

2017· article· en· W2619500366 on OpenAlexvenueno aff
Jin‐Sung Kim, Dongkuk Choi, Sooyong Lee, Jungsun Park

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsnot available
FundersMinistry of Trade, Industry and Energy
KeywordsComposite numberComposite laminatesComposite materialMaterials sciencePlane (geometry)Structural engineeringEngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

Composite materials are widely used in various fields including aerospace and automobiles because they have higher stiffness-to-weight and strength-to-weight ratio than metal materials. Composites can be fabricated to meet design requirements by changing their laminate configurations. For the structural stability of the composite structures, one of reliable failure theories should be applied in order to accurately predict the failure under given loading conditions for any chosen laminate configuration. Over the past several decades, there are numerous failure criteria proposed to more accurately predict the failure of composite laminates. Validity and reliability of composite failure criteria are well studied for in-plane loads. [1, 2] However, similar studies are quite limited in number for out-of-plane loads. In many industrial applications, composite structures are subjected to out-of-plane loads as well as in-plane ones. Mechanical behaviour of composite plates can be quite different depending on loading conditions. Even if a failure criterion is suitable for the inplane loading condition, it cannot be suitable for out-of-plane loads. For this reason, it is necessary to evaluate the validity of the failure criteria for out-of-plane loads.

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 score0.007
Threshold uncertainty score0.901

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 science0.0010.000
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 spread0.201 · 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
Published2017
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicMechanical Behavior of CompositesFrench-language works237,207