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Interlaminar Response of LSI-Produced C/SiC Ceramic Matrix Composites: Experiments and Modelling

2023· article· en· W4386401496 on OpenAlexfundno aff
Marco Riva, A. Airoldi, Antonio Maria Caporale, Lorenzo Cavalli, Mario De Stefano Fumo

Bibliographic record

VenueComposites Part A Applied Science and Manufacturing · 2023
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsnot available
FundersAgenzia Spaziale ItalianaCMC Microsystems
KeywordsMaterials scienceComposite materialDelamination (geology)Bridging (networking)Ceramic matrix compositeComposite numberExperimental dataBendingSilicon carbideCeramicFiber pull-outComposite laminatesComputer science

Abstract

fetched live from OpenAlex

This work investigates the interlaminar properties of a C/SiC composite produced by Liquid Silicon Infiltration, combining experiments based on Double Cantilever Beam tests and numerical analyses. Experimentally, a method to obtain pre-cracks with sharp tips at precise locations is proposed, and specimens with different thickness are used to investigate the effects of bending stress states in the delamination process. The properties of tri-linear Cohesive Zone Models for the modelling of delamination are identified numerically, by using automatic regression techniques without requiring additional assumptions or testing. Fiber bridging effects were observed and modelled, including the evaluation of the process zone lengths with different experimental, analytical, and numerical methods. Overall, the work provides a qualitative insight in the delamination process of long fiber reinforced C/SiC laminates produced with a cost-affordable technique and proposes an experimental and numerical protocol to characterize and model delamination phenomena, taking into account the scattering of material properties.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.268
Teacher spread0.240 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

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