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Record W2802195577 · doi:10.1139/tcsme-2016-0049

THE SYSTEMATIC DESIGN OF PLANETARY-TYPE GRINDING DEVICES FOR OPTICAL FIBER FERRULES AND WAFERS

2016· article· en· W2802195577 on OpenAlexvenueno aff
Long–Chang Hsieh, Tzu-Hsia Chen

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPolishingGrindingFerruleWaferMaterials scienceMechanical engineeringOpticsMachiningFiberEngineering drawingOptical fiberEngineeringComposite materialOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

The traditional planetary grinding device can only polish one optical fiber ferrule. The other grinding device with donut polishing trace is also proposed for polishing wafer. This grinding device has a problem, that is, “the polishing qualities of different points on the wafer are not the same”. Hence, this paper proposes a new planetary grinding device for polishing more optical fiber ferrules and more wafers. Based on the kinematics of planetary gear train, the equations of polishing trace and velocity are derived. Then, the velocity deviation percentage (V dp ) is calculated, which is an important design parameter. Area ratio (A R ) is defined as polishing area divided by grinding pad area. The area ratio (A R ) is another important design parameter for designing planetary grinding devices. In this paper, two design examples are used to illustrate the design process. The research results of this paper can provide an experience for the systematic design of planetary grinding devices.

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.

How this classification was reachedexpand

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 score0.887
Threshold uncertainty score0.308

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 head0.018
GPT teacher head0.213
Teacher spread0.195 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicAdvanced Surface Polishing TechniquesFrench-language works237,207