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Record W2024485013 · doi:10.1115/1.1347034

Geometric Simulation of Ball-End Milling Operations

2000· article· en· W2024485013 on OpenAlexaff
Behnam Moetakef Imani, M.A. Elbestawi

Bibliographic record

VenueJournal of Manufacturing Science and Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBall (mathematics)MachiningEnd millingComputer scienceMechanical engineeringNumerical controlEngineering drawingEngineeringGeometryMathematics

Abstract

fetched live from OpenAlex

In this paper, B-rep solid modeling techniques are used to deal with geometric modeling issues encountered in ball-end milling simulation. The precise B-rep model of the cutter swept volume is developed using advanced sweeping/skinning techniques. Semi-finishing operations are simulated by performing consecutive Boolean operations between the updated part and swept volume. The instantaneous chip geometry is accurately and reliably extracted from the B-rep model of the updated part. Also, the material removal in ball-end milling is precisely simulated for finishing operations, in order to construct the feed-mark and scallop geometries. The validity of the final model is confirmed by comparing the predicted feed-mark profile with experimental measurements. The system developed can be used to verify and optimize NC codes, thus contributing to improving reliability, accuracy, and productivity in CNC machining.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations61
Published2000
Admission routes1
Has abstractyes

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