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Record W7162098817 · doi:10.82308/36440

Understanding and evaluating the changing characteristics of wind-driven rain loads in a warmer climate for Canada

2021· dissertation· en· W7162098817 on OpenAlexaboutno aff
Tarek Dukhan

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeGlobal warmingMoisturePrecipitationClimate zonesClimate modelWater content

Abstract

fetched live from OpenAlex

The amount of rainfall that passes through a vertical plane, during the co-occurrence of rain and wind, is defined as Wind-driven rain (WDR). WDR is the most important moisture source affecting the performance of building façades, and can lead to several undesired results for buildings. In future, higher climate variability and more extreme events are expected. Therefore, Hygrothermal and durability analysis of façades require quantification of future WDR loads for a changing climate. This study evaluates the changing characteristics of WDR loads across Canada for the end of century using an ensemble of regional climate model simulations for the Representative Concentration Pathway 8.5 emissions scenario. The regional climate model, i.e. the Global Environmental Multiscale model, is validated by comparing model-simulated WDR-related climate variables with observations and reanalysis products. The validation results provide confidence in using the model to assess the projected changes to WDR loads for Canada, albeit some biases. Three types of WDR loads, based on semi-empirical equations, are considered in this study: (1) omnidirectional WDR, (2) directional WDR and (3) WDR spells. Omnidirectional and directional WDR amounts are calculated over periods of interest. The former indicates WDR exposure of a specific region, while the latter represents the potential moisture content of absorbent surfaces since it takes into account the façade orientation and wind direction. The WDR spell amounts are representative of the probability of rain penetration through the façade and more critical for design purposes. Furthermore, 3-year return levels of annual maximum WDR spell loads are also used to develop WDR risk category maps for Canada and specifically for 16 Canadian cities. Future projections suggest large increases in WDR loads for some regions of Canada. The increases in these loads are mainly due to increases in both rainfall and wind magnitudes for Arctic Canada, while for other regions it is mostly due to changes in rainfall. Results indicate a shift in the timing of the highest monthly WDR loads from summer to fall. This suggests higher WDR penetration through wall systems, given the relatively low evaporation rate in fall compared to summer even in a warmer climate. Detailed city-level analysis of directional WDR loads suggests large increases for the most critical façade orientations for most of the sixteen cities considered, with the largest increases for those along the east and west coast. The projected changes to the characteristics of future WDR spells imply more severe extreme WDR events and higher deterioration risk. Furthermore, the developed WDR risk category maps help identify façade orientations with elevated risk in future climate which is crucial for the development of detailed guidelines to ensure climate-resilient buildings

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.048
GPT teacher head0.285
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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