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Record W2412758731 · doi:10.7736/kspe.2016.33.6.447

3-Axis Milling Algorithm Development for Carbon Fiber Reinforced Polymer (CFRP) Composites

2016· article· en· W2412758731 on OpenAlexaff
Shan Luo, Reza Bayesteh, Zuomin Dong, Martin Byung‐Guk Jun

Bibliographic record

VenueJournal of the Korean Society for Precision Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComposite materialMaterials scienceCarbon fiber reinforced polymerPolymerComposite number

Abstract

fetched live from OpenAlex

The simulation of Carbon fiber reinforced polymer (CFRP) machining facilitates the selection of optimal cutting parameter for high machining efficiency and better surface quality. In this study, This paper proposes a dual-dexel model to represent the fiber laminate with computational geometry method to calculate the fiber length removed per revolution and fiber cutting angles. A flat end milling simulation software is developed in C# to simulate and display the CFRP milling process. During simulation, fiber lengths, fiber cutting angle and engaged cutting angle can be displayed in real-time. A CFRP plate with different angles in different layer is used to compare the simulation results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of the Korean Society for Precision EngineeringSame topicAdvanced machining processes and optimizationFrench-language works237,207