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Record W2016984368 · doi:10.1115/imece2004-59340

Kinematic Model of Dynamic Drilling Process

2004· article· en· W2016984368 on OpenAlexafffund
Jochem C. Roukema, Yusuf Altıntaş

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaPratt and Whitney Canada
KeywordsThrustKinematicsTorqueVibrationDrillingDrillAxial symmetryMechanicsMachiningStructural engineeringEngineeringControl theory (sociology)PhysicsMechanical engineeringComputer scienceAcousticsClassical mechanics

Abstract

fetched live from OpenAlex

A mathematical model of the torsional-axial chatter vibrations in drilling is presented. The model considers the exact kinematics of both rigid body, and coupled torsional and axial vibrations of the drill. The drill is modeled as a pretwisted beam that exhibits axial deflections due to torque and thrust loading. A mechanistic cutting force model is used to model the cutting torque and thrust as a function of feedrate, speed, radial depth of cut, and drill geometry. The drill rotates and feeds axially into the workpiece while the structural vibrations are excited by the cutting torque and thrust force. The exact location of the drill edge is predicted using the model, and the generated surface is digitized at discrete time intervals. The distribution of chip thickness, which is affected by both rigid body motion and structural vibrations, is evaluated by subtracting the presently generated surface from the previous one. The model considers nonlinearities in cutting coefficients, tool jumping out of cut and overlapping of multiple regeneration waves. The dynamic chip thickness obtained from the true kinematics model allows simultaneous prediction of force, torque, power and dimensional form errors left on the surface. The time domain simulation model allows prediction of stability lobes. The paper provides details of the mathematical model, supported by experimental results of both stable and unstable cuts.

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: Methods · Consensus signal: none
Teacher disagreement score0.814
Threshold uncertainty score0.208

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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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
GenreMethods

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

Citations10
Published2004
Admission routes2
Has abstractyes

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