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Record W4246958685 · doi:10.1016/s1365-6937(04)00314-4

Alfa Laval, Sweden

2004· article· en· W4246958685 on OpenAlexaboutno aff

Bibliographic record

VenueFiltration Industry Analyst · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceRoot mean squareWind speedAccelerationSpectral densityAeroelasticityDeckStormGirderFrequency domainPhysicsDisplacement (psychology)Structural engineeringGeologyMathematicsMeteorologyMechanicsGeodesyEngineeringStatisticsAerodynamicsClassical mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

As Storm Tor struck the western coast of Norway, wind speeds and bridge deck accelerations along the Hardanger Bridge girder were recorded by the monitoring system installed on the bridge. Using 13.5 h of data, mean wind speed, turbulence intensities, gust factor, turbulence length scales, angle-of-attack, and one-point and two-point turbulence spectra are studied using 10-minute stationary averaging intervals. Using the measured turbulence statistics as inputs, the buffeting response of the bridge deck is calculated in the frequency domain. The calculated response is compared with the measured response in terms of the root-mean-square (RMS) of acceleration and displacement components and the power spectral density of the acceleration response. Significant discrepancies are found in the case of the vertical response. Predicting the spectral response is found to be more difficult than predicting the RMS response, in particular for high-frequency responses. Considering the spanwise non-uniformity of turbulence statistics did not affect the predictions significantly.

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 score0.126
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)0.0040.001

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 head0.247
Teacher spread0.228 · 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
Published2004
Admission routes1
Has abstractyes

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