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Determination of an Optimum Geometrical Arrangement of Workpiece in the Ultrasonic Elliptic-Vibration Shoe Centerless Grinding

2004· article· en· W2118247032 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

VenueKey engineering materials · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsGrindingMaterials scienceVibrationMechanical engineeringUltrasonic sensorAcousticsComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract. This paper clarifies the influence of the geometrical arrangement of the workpiece on workpiece roundness in the ultrasonic elliptic-vibration shoe centerless grinding, and determines an optimum geometrical arrangement for minimizing the roundness error of the workpiece. The influence of the geometrical arrangements (, , ) of the workpiece on workpiece roundness were investigated by computer simulation involving a cylindrical workpiece of 5 mm in diameter with an initial roundness error of 25 µm. The results indicated that the final roundness error of the workpiece after grinding reaches a minimum at +=7 ° for various values of . It was found that the smaller the blade angle , the more precise the workpiece in terms of final roundness. Practical grinding operations involving pin shaped workpieces, such as SKH51, 5 mm in diameter and 15 mm in length, were carried out on the experimental apparatus previously developed. The experimental results agreed closely with those obtained by the simulation, showing that the optimum geometrical arrangement of the workpiece can be determined at +=7 ° and =60°, in which the workpiece roundness was improved from an initial roundness error of 25 µm to the final one of approximately 0.6 µm.

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 score0.702
Threshold uncertainty score0.465

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 head0.008
GPT teacher head0.221
Teacher spread0.213 · 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