MétaCan
Menu
Back to cohort
Record W2799504978 · doi:10.1139/tcsme-2008-0034

FINITE ELEMENT CHIP FORMATION ANALYSIS FOR HIGH SPEED MILLING OPERATIONS

2008· article· en· W2799504978 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Machining and Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsFinite element methodEnhanced Data Rates for GSM EvolutionMechanical engineeringHigh-speed steelHardened steelMachiningChip formationEnd millChipTool wearMaterials scienceEnd millingCutting toolEngineeringStructural engineeringMetallurgy

Abstract

fetched live from OpenAlex

High speed end milling of hardened steel offers several advantages over EDM in die/molds applications especially due to recent development in machine tools, spindles and controllers. However successful implementation of this technology is limited mainly due to faster tool wear and undesirable surface properties. Finite element modeling and simulation techniques are capable of optimizing the cutting conditions and tool geometry by predicting the temperature and stresses distributions. In this study a finite element model has been developed to predict cutting forces, temperature and stresses distributions in flat end milling processes of hardened steel using PCBN at high cutting speeds. High speed end milling experiments were conducted using flat bottom end mills with single insert having straight cutting edge. Comparison of simulated and experimental cutting forces data shows reasonable agreement at high speed regime using the developed model.

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: Methods · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.459

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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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