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Record W2131209174 · doi:10.2514/6.2006-979

Micro and Macro Hardness Measurements, Correlations, and Contact Models

2006· article· en· W2131209174 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venue44th AIAA Aerospace Sciences Meeting and Exhibit · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMacroMaterials scienceComputer scienceProgramming language

Abstract

fetched live from OpenAlex

Brief reviews of Brinell (Meyer) and Rockwell indenters and macrohardness tests, Berkovich, Knoop and Vickers indenters and microhardness tests, and nanoindentation tests using the Berkovich indenter are given. Vickers, Brinell and Rockwell C indentation results for Ni 200, SS 304, Zr-4, and Zr-Nb are reported and correlation equations for mi-cro and macrohardness versus penetration depth are given. Temperature effects on yield strength, Brinell and Vickers hardness are given and correlation equations are presented to account for elevated temperatures. Models are presented for calculation of the appro-priate value of contact microhardness which depends on apparent contact pressure and the effective surface roughness of the joint. Examples are given to illustrate the use of the correlation equations. Nomenclature A surface area of a single tube, m2 Aa, AcAV apparent area, contact area, m2 a contact radius, m B unloading curve correlation coefficient Cc dimensionless contact conductance, Cc = σhc/mks CT correlation coefficient, ◦C−1 ◦C degree Celsius cp, cv specific heats at constant pressure and volume, J/kgK c1 Vickers correlation coefficient, GPa c2 Vickers size index

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.611

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 head0.025
GPT teacher head0.206
Teacher spread0.182 · 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