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Record W1996937036 · doi:10.1115/1.2917285

An Acoustic Emission-Based Method for Determining Contact Between a Tool and Workpiece at the Microscale

2008· article· en· W1996937036 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
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of Victoria
FundersNational Institute of Standards and Technology
KeywordsMicroscale chemistryAcoustic emissionSurface (topology)Surface roughnessOvershoot (microwave communication)Surface finishAcousticsMaterials scienceMechanical engineeringComputer scienceGeometryEngineeringPhysicsMathematicsComposite material

Abstract

fetched live from OpenAlex

An acoustic emission-based touch-off detection system has been developed to determine contact between a rotating microtool and a workpiece surface with micron-level accuracy. The system has been implemented on an existing three-axis microscale machine tool. The system has been tested with microendmills as small as 50μm in diameter and microdrills as small as 254μm in diameter. The accuracy of the system has been found to depend on tool geometry and workpiece surface characteristics and is generally on the order of 1μm. An analytical model has been constructed to predict touch-off detection error. The calibrated model has been shown to predict surface overshoot and undershoot trends quite well. Simulations have shown that touch-off error is dominated by part surface roughness.

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 score0.372
Threshold uncertainty score0.330

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 communication0.0000.000
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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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