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Record W2772710346 · doi:10.3390/fib5040046

Influence of Cutting Temperature on the Tensile Strength of a Carbon Fiber-Reinforced Polymer

2017· article· en· W2772710346 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

VenueFibers · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversité du Québec à Trois-RivièresÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceComposite materialEpoxyAbrasiveUltimate tensile strengthTrimmingDelamination (geology)Tool wearCarbon fibersDiamondComposite numberMachiningMetallurgyMechanical engineering

Abstract

fetched live from OpenAlex

Carbon fiber-reinforced plastics (CFRP) have seen a significant increase in use over the years thanks to their specific properties. Despite continuous improvements in the production methods of laminated parts, a trimming operation is still necessary to achieve the functional dimensions required by engineering specifications. Laminates made of carbon fibers are very abrasive and cause rapid tool wear, and require high cutting temperatures. This creates damage to the epoxy matrix, whose glass-transition temperature is often recognized to be about 180 °C. This study aims to highlight the influence of the cutting temperature generated by tool wear on the surface finish and mechanical properties obtained from tensile tests. Trimming operations were performed on a quasi-isotropic 24-ply carbon/epoxy laminate, of 3.6 mm thickness, with a 6 flutes diamond-coated (CVD) cutter. The test specimens of 6 mm and 12 mm wide were obtained by trimming. The reduced width of the coupons allowed amplification of the effect of defects on the measured properties by increasing the proportion of coupon cross-section occupied by the defects. A new tool and a tool in an advanced state of wear were used to generate different cutting temperatures. Results showed a cutting temperature of 300 °C for the new tool and 475 °C for the worn tool. The analysis revealed that the specimens machined with the new tool have no thermal damage and the cut is clean. The plies oriented at −45° presented the worst surface finish according to the failure mode of the fiber. For the worn tool, the surface was degraded and the matrix was carbonized. After cutting, observations showed a degraded resin spread on the machined surface, which reduced the surface roughness and hid the cutting defects. In support of these observations, the tensile tests showed no variation of the mechanical properties for the 12 mm-wide specimens, but did show a 10% loss in mechanical properties for the 6 mm-wide specimens. These results suggest that the thermal defects caused by tool wear affect tensile properties, but only from a certain coupon width below which the machining defects increase their influence on the properties.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.847
Threshold uncertainty score0.248

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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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