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Record W6996959963

\tContributions Towards a Large Eddy Simulation Best Practice Guide for the Numerical Prediction of Wind Loads on Tall Buildings

2020· article· en· W6996959963 on OpenAlexaboutno aff

Bibliographic record

VenuemediaTUM (Technical University of Munich) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceWind engineeringLarge eddy simulationComputational fluid dynamicsFlow (mathematics)Time domainDomain (mathematical analysis)
DOInot available

Abstract

fetched live from OpenAlex

The influence of the domain height and width, and mesh and time step size on the results of a LES (Large-Eddy Simulation) to estimate wind loads on tall buildings was investigated. The results shall contribute to a future LES BPG (Best Practice Guide). Therefore, the wind flow around the CAARC Standard Tall Building, a well-established benchmark, was simulated with the software package Star-CCM+. The CDRFG (Consistent Discrete Random Flow Gener- ation Technique) was used to generate a turbulent inflow. The obtained results showed a good agreement with measurements from the BLWT (Boundary Layer Wind Tunnel) at the University of Western Ontario, Canada. Thus, the results indicated that the well-known rec- ommendations regarding the height and width of the computational domain could be reduced for LES. Moreover, potential fields for further research in the field of wind load estimation with LES were detected. For example, the choice of the most suitable selection of mesh sizes throughout the domain to obtain reasonable results and maintain an acceptable running time of the simulation.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.672
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2020
Admission routes1
Has abstractyes

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