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Record W4407379906 · doi:10.1080/15440478.2025.2461493

Analysis of Entry and Exit Hole Delaminations During Drilling of Jute/Palm Fiber Reinforced Hybrid Composites Using HSS Drill Bits

2025· article· en· W4407379906 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

VenueJournal of Natural Fibers · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsÉcole de Technologie Supérieure
FundersUnited Arab Emirates University
KeywordsComposite materialDrillingMaterials scienceDrillFiberDelamination (geology)PalmDrill holeDrill bitGeology

Abstract

fetched live from OpenAlex

The purpose of this study is to explore drilling defects in hybrid jute/palm fiber composites and propose practical solutions for enhancing machining outcomes. This work is novel in its detailed analysis of delamination, fiber pull-out, and surface fluffing using HSS drills. The results reveal significant differences in delamination factors between the entrance (jute fibers) and exit (palm fibers) under varying machining conditions. Quantitative analysis reveals that optimal conditions for minimizing delamination occur at a spindle speed of 2388 rpm and feed rate of 0.04 mm/rev, achieving delamination factors of 1.121 (entrance) and 1.069 (exit). These findings emphasize the critical role of machining parameters in controlling drilling defects and improving the integrity of hybrid composite materials. Using Response Surface Methodology, predictive models identified feed rate as the dominant factor. Optimizing resin application improved structural integrity and reduced defects, offering experimental evidence for industrial applications in sustainable hybrid composite manufacturing.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.402

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.237
Teacher spread0.232 · 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