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Record W2081155466 · doi:10.1115/1.2738961

An Experimental Evaluation of an Atomization-Based Cutting Fluid Application System for Micromachining

2008· article· en· W2081155466 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

VenueJournal of Manufacturing Science and Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsUniversity of Victoria
FundersUniversity of Illinois at Urbana-Champaign
KeywordsCutting fluidViscosityMaterials scienceSurface tensionMechanical engineeringSurface micromachiningPetroleum engineeringComposite materialMachiningGeologyMetallurgyEngineeringFabricationThermodynamics

Abstract

fetched live from OpenAlex

An atomization-based cutting fluid application system is developed for micro-end milling. The system was designed to ensure spreading of the droplets on the workpiece surface based on the analysis of the atomized droplet impingement dynamics. The results of the initial experiments conducted to examine the viability of the system show that the cutting forces are lower and tool life is significantly improved with the atomized cutting fluids when compared to dry and flood cooling methods. Also, application of atomized cutting fluid is found to result in good chip evacuation and lower cutting temperature. Experiments were also conducted to study the effect of fluid properties on cutting performance, and the results show that cutting fluids with lower surface tension and higher viscosity perform better in terms of cutting forces.

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)0.001
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: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.242
Teacher spread0.231 · 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