MétaCan
Menu
Back to cohort
Record W2537024620 · doi:10.11159/icsenm16.113

The Influence of Borax Filler Addition on Damping and Vibration Response of S-glass/epoxy Composite Laminates

2016· article· en· W2537024620 on OpenAlexvenueno aff
Ahmet Erkliğ, Mehmet Bulut

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
Fundersnot available
KeywordsComposite materialEpoxyMaterials scienceComposite numberBoraxVibrationFiller (materials)Composite laminatesAcousticsPhysics

Abstract

fetched live from OpenAlex

This study aims to examine the influence of borax addition on damping and vibration response of S-glass/epoxy composite laminates. Natural frequency and damping response of particle filled composite laminates cantilever beam are determined with different mass ratios between borax and epoxy resin with hardener. Borax particles were used as replacement material with epoxy resin and their particle loadings (the ratio between mass of the borax over total mass of the epoxy with hardener+borax filler) of the samples were 0 (plain), 5, 10, 15 and 20 mass %, respectively. Vibration properties of samples were experimentally determined by using modal analysis procedures. For damping responses, half power band-width method was employed with first natural frequency value. The results indicated that the replacement of boron particles with epoxy resin by 5 mass % of particle loading" significantly increased the damping and natural frequency and further increase of borax content caused a reduction in damping and vibration values.

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 score0.108
Threshold uncertainty score0.350

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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicNatural Fiber Reinforced CompositesFrench-language works237,207