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Record W2315264924 · doi:10.1061/9780784412626.024

A Parametric Representation of Wind-Driven Rain in Experimental Setups

2012· article· en· W2315264924 on OpenAlexaff
Thomas Baheru, Arindam Chowdhury, Girma Bitsuamlak, Ali Tokay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsFacadeEnvironmental scienceWind speedMeteorologyParametric statisticsComputational fluid dynamicsBuilding envelopeTurbulence kinetic energyComputer scienceMarine engineeringTurbulenceEngineeringAerospace engineeringCivil engineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

The study of wind-driven rain (WDR) has shown a significant progress in past few decades. The applications of semi-numerical and computational fluid dynamics (CFD) methods have shown major advances to reasonably estimate the amount WDR impinging on building facade. The agreement witnessed between numerical results and actual measurements on existing buildings reinforces the above fact. However, standardized testing methodology for WDR which can produce reliable and repeatable test results is still in its development stage. Buildings' component-wise testing methods for WDR effects prescribed in standards and building codes are limited to a simplified application of water with a uniform and cyclic static pressure. The study presented herein focuses on the representation of WDR and the different parameters involved in simulation of WDR in full and large-scale testing facilities. As to the holistic testing approach, many parameters are involved in determining the amount of rain water deposition on building envelope. These parameters consist of wind field characteristics (wind speed profile and turbulence intensity), rain rate, raindrop size spectrum and its integral parameters (drop number concentration and liquid water content per unit volume of air, mean-weight and volume median diameters etc.) and rain duration. The terminal raindrops velocity also has a direct effect on the calculations of WDR rate and in the determination of the level of impact caused by raindrops on building façade. The paper also discusses the processes involved in hurricane level WDR simulation using a 2-fan WDR generator at Florida International University (FIU). The objective is to develop flow management techniques using a 2-fan prototype system that can be applied to simulate the target parameters at the large-scale 12-fan Wall of Wind hurricane wind and rain simulator. WDR is generated using different type of nozzles arranged in a grid pattern with a controlled discharge rate. Rainfall data (drop size distribution and rain rate) collected during tropical cyclones have been used as target for simulating realistic WDR at the testing facility and preliminary results are presented and discussed.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
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)0.0010.000

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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.

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

Citations7
Published2012
Admission routes1
Has abstractyes

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