A Parametric Representation of Wind-Driven Rain in Experimental Setups
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".