Impact of upstream buildings on Wind-Driven Rain Loading: Refining Obstruction Factor in ISO semi-empirical model based on CFD
Bibliographic record
Abstract
CFD is a valuable tool for assessing Wind-Driven Rain (WDR) loading, one of the most important environmental loads for façade design. The majority of previous studies on this topic have primarily concentrated on simple building configurations, i.e., stand-alone buildings. Hence, prior findings may not be applicable to consider the impact of upstream buildings in urban areas, which significantly alter wind flow field, consequently, change WDR loadings on downstream building facades compared to the stand-alone building. Part A : four different steady-state RANS models (i.e., standard k − ω , realizable k − ε , RNG k − ε , and standard k − ε ) coupled with the Eulerian Multiphase (EM) technique (RANS-EM) are compared and implemented using OpenFOAM-7. These models are validated and verified based on wind-tunnel and field measurement data obtained from the literature for a six-story mid-rise residential building located in an urban area in Vancouver, Canada. The study considers 13 distinct rainfall events, for the test building with/without overhangs. All four RANS models are deemed suitable for modeling WDR in urban areas, while the steady-state standard k-ω RANS-EM approach without incorporating turbulent dispersion showing slightly better performance, thus utilized for the reminder of the study. Part B : a sensitivity analysis is presented on how the upstream buildings influence the WDR loading on a downstream building, denoted as Obstruction Factor. A comparison between the CFD and ISO semi-empirical model shows significant discrepancies, potentially reaching up to factors of 5. Thus, updated Obstruction Factors are suggested to enhance the ISO model for more accurate estimation of WDR loads.
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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) | 0.000 | 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".