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Record W3213739883 · doi:10.1115/imece2001/med-23304

An Improved Time Domain Simulation for Dynamic Milling at Small Radial Immersions and Large Depths of Cut

2001· article· en· W3213739883 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

VenueManufacturing engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsKinematicsDiscretizationVibrationTime domainImmersion (mathematics)Deflection (physics)MechanicsStability (learning theory)Control theory (sociology)Materials scienceDynamic simulationComputer scienceSimulationAcousticsPhysicsGeometryMathematicsOpticsClassical mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

Abstract This paper presents an improved time domain model for milling, which can simulate vibratory cutting conditions at very small radial widths of cut and large depths of cut. The improved kinematics model allows simulation of very small radial immersions. The varying dynamics modeled along the cutting depth allows milling with very flexible cutters and/or flexible workpieces at very deep cuts to be simulated. The model can predict forces, surface finish, and chatter stability, accurately accounting for non-linear effects that are difficult to model analytically. The discretized cutter and workpiece kinematics and dynamic models are used to represent the exact trochoidal motion of the cutter, and to investigate the effects of forced vibrations and changing radial immersion due to deflection and vibrations on chatter stability. Three dimensional surface finish profiles are predicted and are compared to measured results. Stability lobes generated from the time domain simulation are also shown for various cases.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.482
Threshold uncertainty score0.765

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 head0.004
GPT teacher head0.213
Teacher spread0.209 · 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