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Record W3131466498 · doi:10.3389/fbuil.2020.620071

An Examination of the Gust Effect Factor for Rigid High-Rise Buildings

2021· article· en· W3131466498 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Built Environment · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsAerodynamicsAdmittanceDragLoad factorStructural engineeringEngineeringTurbulenceScale factor (cosmology)MechanicsPhysicsAerospace engineering

Abstract

fetched live from OpenAlex

In order to systematically investigate the gust effect factor for rigid buildings, the derivation of the gust effect factor in ASCE 7–16 is carefully reviewed and scale model pressure tests were carried out for rectangular-plan high-rise buildings with plan aspect ratios ranging from 0.11 to 9. The gust effect factor and the aerodynamic admittance function (AAF) for area-averaged pressure coefficients and base drag coefficients were obtained and discussed in detail. The results show that the AAF has direct influence on the value of the gust effect factor, depending on whether effects of non-contemporaneous gust actions or body-generated turbulence are playing a leading role. The ASCE 7–16 gust effect factor for rigid buildings underestimates the measured values for individual walls due to differences in the AAF, peak factors, and the employment of the 3 s moving average filter. However, the ASCE 7–16 gust factor for overall drag is estimated within 5% or better.

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 score0.196
Threshold uncertainty score0.481

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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