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Record W2006724892 · doi:10.1243/09544054jem931

Arbitrary Lagrangian Eulerian analysis on cutting with a honed tool

2008· article· en· W2006724892 on OpenAlexfundno aff
Hossam A. Kishawy, Ibrahim Deiab, A.J. Haglund

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnhanced Data Rates for GSM EvolutionChip formationMaterials scienceShear zoneTrailing edgeMechanicsShear (geology)Shear stressFinite element methodStagnation pointViscoplasticityGeometryComposite materialGeologyStructural engineeringMachiningMetallurgyEngineeringTool wearMathematicsPhysicsConstitutive equation

Abstract

fetched live from OpenAlex

A thermo-elasto-viscoplastic two-dimensional finite element analysis of the effects of different edge radii on the mechanics of orthogonal metal cutting is presented. The shear stress distribution was used to quantify the stagnation point as well as the minimum chip thickness needed to form a chip when using a honed cutting edge. The determined location of the stagnation point using the shear stress distribution agrees well with location calculated using the velocity profile in the vicinity of the cutting edge. The plastic flow of the material around the honed cutting edge and below the machined surface was studied. The ploughing force generated while cutting with a carbide tool was calculated. Contour plots of stress, strain, temperature, and velocity in the cutting zone were analysed along with contact stresses and temperature profiles on the rake face.

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: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.182
Teacher spread0.176 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering ManufactureSame topicAdvanced machining processes and optimizationFrench-language works237,207