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Record W2057437493 · doi:10.1115/imece2002-39109

Analysis of the Machining Process Using a Thermo-Elastic-Viscoplastic Finite Element Model

2002· article· en· W2057437493 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 · 2002
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsFinite element methodViscoplasticityMaterials scienceMachiningCeramicPlane stressDeformation (meteorology)Stress (linguistics)Chip formationThrustEnhanced Data Rates for GSM EvolutionStress–strain curveComposite materialMechanical engineeringStructural engineeringTool wearConstitutive equationMetallurgyEngineering

Abstract

fetched live from OpenAlex

A plane-strain thermo-elasto-viscoplastic finite element model has been developed and used to simulate orthogonal machining. Simulations of cutting 304L stainless steel have been carried out using sharp, chamfered, and honed ceramic tools. Employing a combined thermal and mechanical stress analysis with temperature-dependent physical properties, the finite element model is used to investigate the effect of process parameters, tool geometry and edge preparation on the machining process. Stress and strain distributions within the chip and the elastic tool are presented. In addition, trends in the cutting and thrust forces, contact stress distributions and the plastic deformation beneath the machined surface are studied.

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 score0.620
Threshold uncertainty score0.516

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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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