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Record W2030487102 · doi:10.1115/1.2806252

Optical Microscopy-Aided Indentation Tests

2008· article· en· W2030487102 on OpenAlex
Darrel A. Doman, Robert Bauer, Andrew Warkentin

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Engineering Materials and Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIndentationFinite element methodMaterials scienceEnhanced Data Rates for GSM EvolutionOptical microscopeCeramicPlasticityContact areaStructural engineeringMechanical engineeringComposite materialEngineeringScanning electron microscope

Abstract

fetched live from OpenAlex

The contact characteristics of ceramic-metallic interactions are of critical importance in the design of high-speed ceramic rolling contact bearings. This type of interaction is not described well by traditional indentation tests since small displacements and barely discernable indentations are encountered. In this work, an optical microscopy system is described that is used to measure small indenter displacements accurately. Images of the indenter are taken throughout the test and processed using sophisticated edge detection algorithms to accurately determine the position of the center of the indenter. Thus, the indenter displacements on the order of 1μm can be measured independent of any structural flexibility present in the test apparatus. Experimental indentation tests using an alumina indenter mounted on a stainless steel post were performed and processed with the optical system. The results were compared to existing analytical models for fully elastic and elastoplastic cases as well as a finite element model developed using a Johnson–Cook plasticity material model. The comparison shows that the analytical models do not predict the experimental results well, whereas the finite element model agrees very well. Subsequent analysis of the finite element model shows that the size of the contact zone and pressure distributions, both very important in the design of bearings, can be more accurately described than the traditional analytical treatments.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.359

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 head0.200
Teacher spread0.193 · 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