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Record W4309460216 · doi:10.3390/wind2040038

Effects of Inflow Parameters and Disk Thickness on an Actuator Disk inside the Neutral Atmospheric Boundary Layer

2022· article· en· W4309460216 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

VenueWind · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInflowActuatorMomentum (technical analysis)MechanicsConvergence (economics)Boundary layerLogarithmControl theory (sociology)TurbinePower (physics)Materials scienceComputer sciencePhysicsMechanical engineeringMathematicsEngineeringMathematical analysisThermodynamics

Abstract

fetched live from OpenAlex

An accurate choice of the inflow parameters has been shown to affect the CFD results significantly. In this study, the actuator disk method (AD) is used to investigate the effects of the widely used inflow formulations, the logarithmic and power-law formulations, in the neutral atmospheric boundary layer simulations. Based on the one-dimensional momentum theory, the AD model is a rapid method that replaces the turbine with a permeable disk and is among the most used methods in the literature. The results of the k-ω AD simulation indicated that in spite of the logarithmic method’s widespread use, the power law formulation gives a better description of the velocity field. Furthermore, an actuator disk thickness study also showed that given the effect of actuator disk thickness on the rate of convergence, more attention should be dedicated towards finding a suitable disk thickness value. The combination of an optimized mesh and a suitable choice of AD thickness can help with the rate of convergence which in turn shortens the simulation’s run time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.358

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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