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Record W649267170 · doi:10.1299/jsmelem.2003.915

513 Effect of Laval Nozzle in Precision Cutting of Thin Metal Plate by Pulsed YAG Laser

2003· article· en· W649267170 on OpenAlexaboutno aff
Yasuhiro Okamoto, Yoshiyuki UNO, Masayoshi Hosogaya, Naoki Miyanagi

Bibliographic record

VenueProceedings of International Conference on Leading Edge Manufacturing in 21st century LEM21 · 2003
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleDrossMaterials scienceMechanical engineeringCylinderMechanicsMach numberFlow (mathematics)EngineeringMetallurgyPhysics

Abstract

fetched live from OpenAlex

Effects of Laval nozzle on assist gas flow and the machined results in precision cutting of thin plate by pulsed YAG laser were experimentally investigated. Assist gas flow from Laval nozzle does not have Mach Shock Disk, and goes more straight than a traditional convergent nozzle. Therefore, the pressure on workpiece increases, since assist gas flow from Laval nozzle can utilize energy more efficiently. However, caution is necessary in setting of cylinder gas pressure, since Laval nozzle has many unstable regions in which the pressure on workpiece changes periodically. Using Laval nozzle makes it possible to reduce the height of dross even under low cylinder gas pressure condition. Thus the consumption of assist gas flow quantity can be reduced. Moreover, it was pointed out that the convexed inner wall of nozzle leads of reduction of dross generation.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations0
Published2003
Admission routes1
Has abstractyes

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