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Record W2769556769 · doi:10.1115/1.4038570

Dynamics of Multipoint Thread Turning—Part I: General Formulation

2017· article· en· W2769556769 on OpenAlex
Mohammad Rezayi Khoshdarregi, Yusuf Altıntaş

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVibrationThread (computing)DiscretizationChipTorqueModalControl theory (sociology)Machine toolMechanical engineeringEngineeringComputer scienceAcousticsMathematicsMathematical analysisMaterials sciencePhysics

Abstract

fetched live from OpenAlex

This paper formulates the generalized dynamics and stability of thread turning operations with custom multipoint inserts. The closed-loop chip regeneration mechanism is modeled by evaluating the effect of the current vibrations and the vibration marks left from the previous tooth. Using the developed chip discretization method, the dynamic cutting and process damping forces are obtained at each point along the cutting edge by projecting the three-dimensional (3D) vibrations of the tool and workpiece in the direction of local chip thickness. The equation of motion is derived in both physical and modal spaces, and stability is analyzed in frequency domain using Nyquist criterion. An iterative process optimization algorithm has been developed to maximize productivity while respecting machine tool's torque and power limits. Extension of the model to thin-walled workpieces along with the validating experiments on real-scale oil pipes is presented in Part II of this paper.

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: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.316

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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