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Effect of Particle Size on the Characteristics of Sand Jets in Water

2011· article· en· W2092641679 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

VenueJournal of Engineering Mechanics · 2011
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTurbulence kinetic energyTurbulenceDissipationMechanicsKinetic energyParticle sizeParticle (ecology)Particle-size distributionLarge eddy simulationComputational fluid dynamicsMaterials sciencePhysicsEnvironmental scienceGeotechnical engineeringGeologyThermodynamicsClassical mechanics

Abstract

fetched live from OpenAlex

Sand jets in water have extensive engineering applications. A detailed numerical modeling of sand jets in water was conducted at high initial sand concentration using a commercial computational fluid dynamics package (ANSYS CFX 11.0). The results of the numerical simulation were first compared with some recent laboratory experiments. Simulations were then conducted to investigate the effect of sand particle sizes on velocity distribution, concentration profile, and turbulent properties. Turbulent flow characteristics, such as turbulent kinetic energy, turbulence intensity, rate of energy dissipation, and turbulent eddy frequency, were evaluated and the trend compared with the previous studies in the literature. The location of maximum kinetic energy was found to be independent of particle size. The turbulent kinetic energy and rate of dissipation of the water phase decrease with increasing particle size.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.321

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 head0.009
GPT teacher head0.192
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