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Record W2617780340 · doi:10.1080/03602559.2017.1332207

The Effects of Micro- and Nano-Fillers’ Additions on the Dynamic Impact Response of Hybrid Composite Armors Made of HDPE Reinforced with Kevlar Short Fibers

2017· article· en· W2617780340 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymer-Plastics Technology and Engineering · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMaterials scienceComposite materialHigh-density polyethylenePolyethyleneKevlarComposite numberCompression moldingNano-

Abstract

fetched live from OpenAlex

Hybrid composite armors consisting of Kevlar short fibers reinforced high-density polyethylene were prepared and the effects of the addition of micro and nano-fillers on the dynamic impact response and the energy absorption under ballistic impact were investigated. Five groups of specimens were manufactured using compression molding of pellets containing mixtures of high-density polyethylene and the reinforcing materials. The first group consist of high-density polyethylene reinforced with 10 wt% Kevlar pulp (KN-1). The rest are hybrid composites created by the addition of 20 wt% of micro and nano-fillers. The natural micro-fillers used are particles of chonta palm wood (KN-2) and potato flour (KN-3). The synthetic nanofillers are colloidal silica (KN-4) and gamma alumina (KN-5). Microstructure (scanning electronic microscope) and compositional (energy-dispersive spectroscopy) analysis of the hybrid composites were carried out to evaluate matrix-reinforcements-interface. The fabricated composites plates were subjected to high velocity impact using split Hopkinson pressure bar system and ballistic impact, according to NIJ standard–0101.06 for ballistic resistance. Significant stiffness improvements of up to 43.5% were achieved as a result of the addition of synthetic nano-particles to Kevlar fiber reinforced high-density polyethylene. X-ray diffractometer analysis revealed that the crystalline structure of the Kevlar reinforced high-density polyethylene is unaffected by addition of the nano-particles as fillers. However the intensity of the crystalline peaks decreased depending on the type of the added fillers. The results of dynamic impact test using split Hopkinson pressure bar revealed improved impact resistance by addition of synthetic nanofillers (silica and alumina). The results of the ballistic impact test showed the gamma alumina nano-particles (KN-5) exhibited the highest energy absorption capability. The results of these investigations indicate that hybridization Kevlar short fibers reinforced high-density polyethylene by micro and nano-fillers addition enhances the stiffness, impact resistance and ballistic energy absorption capability of the composites.

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.

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 score0.005
Threshold uncertainty score0.427

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 studies0.0000.001
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 head0.202
Teacher spread0.199 · 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