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Record W4394690905 · doi:10.3390/jcs8040138

Dynamic Behavior and Permanent Indentation in S2-Glass Woven Fabric Reinforced Polymer Composites under Impact: Experimentation and High-Fidelity Modeling

2024· article· en· W4394690905 on OpenAlexaff
Mohammad Rezasefat, Yogesh Kumar, Amanda Albertin Xavier da Silva, Sandro Campos Amico, James D. Hogan, Andrea Manes

Bibliographic record

VenueJournal of Composites Science · 2024
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsComposite materialMaterials scienceIndentationWoven fabricFidelityComputer science

Abstract

fetched live from OpenAlex

This paper studies the behavior of S2-glass woven fabric reinforced polymer composite under low-velocity impact at 18–110 J energy. A macro-homogeneous finite element model for the prediction of their response is implemented, considering the non-linear material behavior and intralaminar and interlaminar failure modes for the prediction of impact damage. The model accurately predicted the permanent indentation caused by impact. By applying the Ramberg-Osgood formulation, different initial stiffness values are examined to assess the post-impact unloading response. This approach reveals the significant role of initial stiffness in inelastic strain accumulation and its consequent effect on permanent indentation depth. A higher initial stiffness correlates with increased inelastic strain, influencing the impactor rebound and resulting in greater permanent indentation. By accurately predicting permanent indentation, and damage accumulation for different impact energies, this study contributes to a better understanding of the impact behavior of composite materials, thereby promoting their wider application.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.302
Teacher spread0.288 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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