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Micro Ball End Milling of Nickel-Based Alloy for Laval Nozzle

2014· article· en· W2024301145 on OpenAlexaboutno aff
Yu Cai, Zhan Qiang Liu

Bibliographic record

VenueMaterials science forum · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsNozzleBall (mathematics)Materials scienceEnd millingMachiningMechanical engineeringSpray nozzleMilling cutterResidualAlloyMetallurgyEngineeringGeometryComputer science

Abstract

fetched live from OpenAlex

The performance of the micro nozzle is determined primarily by its machined surface topology and geometric profile. A circular cross-section micro-Laval nozzle is modeled and studied by using numerical simulation in this paper. The real residual height and residual area of machined nozzle surface with ball-end milling cutter are proposed. A micro-Laval nozzle was machined successfully. It is found that the ball end milling cutter with large radius is suitable for finishing operations in the viewpoint of nozzle performance. Moreover, the serial process of drilling and milling has been proved by experiments with which both high-level machining accuracy and performance can meet the nozzle requirement.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.460
Threshold uncertainty score0.339

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 head0.007
GPT teacher head0.227
Teacher spread0.221 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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