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Record W2046779525 · doi:10.1299/jamdsm.2.651

Cutting of Solid Type Molded Composite Materials by Q-switched Fiber Laser with High-Performance Nozzle

2008· article· en· W2046779525 on OpenAlexaboutno aff
Yasuhiro Okamoto, Ryoji Kitada, Yoshiyuki UNO, Hiroyuki Doi

Bibliographic record

VenueJournal of Advanced Mechanical Design Systems and Manufacturing · 2008
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceEpoxyNozzleComposite materialComposite numberLaser cuttingLaserSubstrate (aquarium)IrradiationMolding (decorative)OpticsMechanical engineering

Abstract

fetched live from OpenAlex

This paper deals with the effects of the nozzle shape on cutting results and fundamental characteristics of laser cutting of solid type molded composite materials, which was composed of semiconductor board and epoxy-resin molding compounds, by Q-switched single-mode fiber laser. Experimental results clarified that high speed cutting of 16 mm/s could be carried out using a Laval throat nozzle with initial expansion zone, which also led to straighter kerf shape and narrower kerf width than other nozzles. Besides, Laval throat nozzle made it possible to reduce the kerf width, and the difference of kerf width between irradiation-side and exit-side became smaller. Nitrogen assist gas led to the narrow kerf width and straight kerf shape. Furthermore, the difference of kerf between substrate side and epoxy-resin side became smaller. Substrate side irradiation was more suitable for precision cutting than epoxy-resin side irradiation. These results proved that Q-switched single-mode fiber laser was useful for cutting of composite materials.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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 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

Citations24
Published2008
Admission routes1
Has abstractyes

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