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Record W7132056191

One-side cutting strategy for ultraprecise single point cutting of v-grooves case 2: constant cutting area

2019· article· en· W7132056191 on OpenAlexvenueno aff
D. Joao, N. Milliken, O. Remus Tutunea-Fatan, E. V. Bordatchev

Bibliographic record

VenueNPARC · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsConstant (computer programming)Single pointCutting toolPoint (geometry)Groove (engineering)Current (fluid)
DOInot available

Abstract

fetched live from OpenAlex

The current study presents a cutting strategy to be used during V-groove fabrication through ultraprecise single point cutting. The profile of the groove is produced by maintaining a constant cutting area. The experimental results suggest that a correlation between the amount of material removed in each pass and the magnitude of FY exists. However, while from a theoretical standpoint it is reasonable to predict that FY will remain constant since it is directly proportional with the amount of material removed (of a preset constant cutting area), a certain amount of decay in the magnitude of FY was noticeable. This might suggest that the gradually decreasing chip thickness also plays an unforeseen but possibly important role on the cutting force magnitude. In addition, surface topography measurements have confirmed that the proposed strategy can produce ultraprecise surfaces. The analysis presented in the current study sets the foundation for further development of future and more efficient cutting strategies to be used in ultraprecise single point cutting of V-grooves. Furthermore, simulation models of the cutting mechanics will be developed and then validated against the experimentally acquired 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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score0.905

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 head0.025
GPT teacher head0.246
Teacher spread0.222 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

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