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Record W2035084964 · doi:10.1115/1.3159047

Chatter Stability of General Turning Operations With Process Damping

2009· article· en· W2035084964 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

VenueJournal of Manufacturing Science and Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of British Columbia
FundersSandvik Coromant
KeywordsChipChip formationVibrationCutting toolEnhanced Data Rates for GSM EvolutionMachiningMachine toolEngineeringMechanical engineeringStability (learning theory)Structural engineeringControl theory (sociology)Tool wearComputer scienceAcousticsPhysics

Abstract

fetched live from OpenAlex

The accurate prediction of chatter stability in general turning operations requires the inclusion of tool geometry and cutting conditions. This paper presents regenerative chip and regenerative chip area/cutting edge contact length based dynamic cutting force models, which consider cutting conditions and turning tool geometry. The cutting process is modeled as it takes place along the equivalent chord length between the two end points of the cutting edge. The regenerative chip model is simple, and the stability can be solved directly. However, the three-dimensional model considers the effect of tool vibrations at the present and previous spindle revolutions on the chip area, chord length, and force directions and is solved using Nyquist stability criterion. The penetration of worn tool flank into the finish surface is considered as a source of process damping. The effects of the nose radius, approach angle of the tool, and feedrate are investigated. The proposed stability model is compared favorably against the experimental 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.

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 score0.568
Threshold uncertainty score0.298

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 communication0.0000.001
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 head0.223
Teacher spread0.216 · 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