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Record W3135748151 · doi:10.2749/newyork.2019.0585

Wind Loading on Catenary Domes

2019· article· en· W3135748151 on OpenAlexaff
Richard M. van Gool, R. Bradley, Mitchell Gohnert

Bibliographic record

VenueReport · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsCatenaryWind tunnelStructural engineeringDome (geology)RADIUSPressure coefficientGeologyGeometryEngineeringGeotechnical engineeringMathematicsAerospace engineeringComputer science

Abstract

fetched live from OpenAlex

<p>Catenary domes are a less conventional, but structurally efficient, alternative to traditional circular-profile domes. Unlike the more common circular forms, there is a dearth of wind loading information for catenary structures. This paper aims to provide some insight in this regard. A series of wind tunnel tests were undertaken to investigate the effects of geometry and Reynolds number on the mean pressure coefficient distributions over catenary domes in a turbulent boundary layer flow. A hemispherical dome was also assessed, and the results compared with that for the catenary shapes. These parameters were evaluated to elucidate their influence on the loading on these structures. Only the results relating to mean pressure coefficients are reported in this paper. An important finding was that the height to base radius (H/R) of the catenary dome had a substantial influence on the mean pressure coefficient distributions over the structure. Finally, the results of the investigation and their implications on the design of catenary domes are discussed. This may be of value to designers because at present no wind loading information exists for catenary domes</p><p>– at least to the author’s knowledge.</p>

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score1.000

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)0.0010.004

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

Study designObservational
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
Published2019
Admission routes1
Has abstractyes

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