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Record W2127427832 · doi:10.1177/2041297510394057

Porosity and cutting forces: from macroscale to microscale machining correlations

2011· article· en· W2127427832 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

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsMicroscale chemistryMachinabilityMachiningSurface micromachiningPorosityMaterials scienceContext (archaeology)Mechanical engineeringMetallurgyComposite materialFabricationEngineeringGeology

Abstract

fetched live from OpenAlex

Porous metals, typically produced through powder metallurgy, represent a class of relatively new materials with wide industrial applications, lately extending into the microscale domain. Although produced in near-net shapes, most components fabricated from these materials still require some form of secondary machining. Despite the progress made in the field, relatively little is known either on the inherent cutting mechanism or on the behaviour of these materials under micromachining conditions. The present study reviews the main cutting theories proposed in macroscale machining, along with one of the primary parameters used to describe its machinability performances, namely cutting forces. Then, the feasibility of macroscale concepts is discussed in the context of micromachining technology that is characterized by comparable tool and pore sizes. The microslot cutting experiment performed in a porous titanium sample outlined the relative interplay between the magnitude of the cutting force and porosity of the material. Based on this, it was concluded that the impact of structural porosity on cutting forces experienced during micromachining is significant and therefore further in-depth investigations will be required.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.647

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 head0.009
GPT teacher head0.192
Teacher spread0.183 · 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