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Record W2765103588 · doi:10.1115/fedsm2017-69534

Experimental Investigation of the Influence of Inflow Conditions on the Flow Over an Extended Edge Escarpment

2017· article· en· W2765103588 on OpenAlexaff
J. LoTufo, Kamran Siddiqui, Horia Hangan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsEscarpmentTurbulenceInflowTurbineFlow (mathematics)GeometryGeologyLeading edgeTowerMechanicsWakeMeteorologyWind directionWind speedPhysicsGeomorphologyStructural engineeringEngineeringMathematics

Abstract

fetched live from OpenAlex

Mean and turbulent flow behavior over a 1:50 scale model of a wind turbine site containing a local escarpment was investigated from wind directions of 230°, 270° and 300°. Flow from each direction contained vastly different local geometry at the same elevation. Results showed separation regions are formed immediately downstream of the escarpment at each wind direction. It is observed that turbulence within the first 3 meters from the escarpment edge is strongest for inflow from 230° while flow from 300° shows similar trends with lower turbulence magnitude. Inflow from 270° had the most impactful effect on the flow behavior showing the largest wake region increasing in height with the distance from the leading edge. The results also show that the flow field below 55 m was effected by the local geometry of the escarpment leading up to and likely beyond the turbine location. It is concluded that the effects induced from local geometry may cause changes to dynamic loading and fatigue on both the turbine blades and tower.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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