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Record W1988990287 · doi:10.12989/was.2013.17.1.001

Multiscale finite element method applied to detached-eddy simulation for computational wind engineering

2013· article· en· W1988990287 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 and Structures · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Numerical Methods in Computational Mathematics
Canadian institutionsMcGill University
Fundersnot available
KeywordsTurbulenceDiscretizationLarge eddy simulationFinite element methodMechanicsDetached eddy simulationScalar (mathematics)Galerkin methodComputationMeteorologyPhysicsMathematicsEngineeringGeometryReynolds-averaged Navier–Stokes equationsMathematical analysisStructural engineeringAlgorithm

Abstract

fetched live from OpenAlex

A multiscale finite element method is applied to the Spalart-Allmaras turbulence model based detached-eddy simulation (DES). The multiscale arises from a decomposition of the scalar field into coarse (resolved) and fine (unresolved) scales. It corrects the lack of stability of the standard Galerkin formulation by modeling the scales that cannot be resolved by a given spatial discretization. The stabilization terms appear naturally and the resulting formulation provides effective stabilization in turbulent computations, where reaction-dominated effects strongly influence near-wall predictions. The multiscale DES is applied in the context of high-Reynolds flow over the Commonwealth Advisory Aeronautical Council (CAARC) standard tall building model, for both uniform and turbulent inflows. Time-averaged pressure coefficients on the exterior walls are compared with experiments and it is demonstrated that DES is able to resolve the turbulent features of the flow and accurately predict the surface pressure distributions under atmospheric boundary layer 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.420
Threshold uncertainty score0.589

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 head0.019
GPT teacher head0.309
Teacher spread0.290 · 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