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Record W2915030936 · doi:10.5006/2864

Parametric Wall Shear Stress Characterization of the Rotating Cage Test Method

2019· article· en· W2915030936 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

VenueCORROSION · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsCageCorrosionMaterials scienceParametric statisticsCarbon steelShear stressShear (geology)Structural engineeringComposite materialMechanicsMetallurgyEngineeringPhysicsMathematics

Abstract

fetched live from OpenAlex

The rotating cage is a standardized methodology for investigating the corrosion of metals under pipe flow conditions. Average corrosion rates are determined through mass loss, and the relatively large surface area of the specimens permits statistical analysis of localized corrosion phenomena, monitored through techniques such as laser profilometry. The shear stress of the moving fluid on the metal coupons is commonly used to relate experimental test conditions to those of flowing pipelines. This paper presents a parametric study of computational fluid dynamics simulations that investigated the dependence of the wall shear stress (both the area-weighted average and 90th percentile) on rotational velocity, fluid viscosity, and fluid density for the standardized rotating cage test apparatus. The conditions covered the full range of rotational speeds of the apparatus, over a wide range of pipeline fluids and operating temperatures. The parametric characterization of the rotating cage is presented in a single chart, like that of the Moody chart for pipe flows.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.215

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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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