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Assessing Water Loads Post-Flooding in Envelope Assemblies: Effects of Interstices and Hydrostatic Pressure

2025· article· W4415369194 on OpenAlexaffabout
Dominique Derome

Bibliographic record

VenueUCL Open Environment · 2025
Typearticle
Language
FieldEngineering
TopicWater Systems and Optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsEnvelope (radar)Flood mythHydrostatic pressureHydrostatic equilibriumDrainageResidualThermocoupleHydraulics

Abstract

fetched live from OpenAlex

Recurring floods and increasing disaster management costs highlight the need for resilient building envelope assemblies, and this also applies to Québec, Canada. This study investigates the effects of hydrostatic pressure and interstitial gaps between materials on water loads, and drying behaviour on the occurrence of damage (e.g., swelling, mould growth) in building assemblies. Based on flood event scenarios, individual envelope components were exposed to varying water levels and durations to document the effect of hydrostatic pressure. Neutron imaging was employed to visualize water drainage and residual water trapped within interstices. Additionally, a dedicated experimental setup with 80 thermocouples and 20 probes was utilized under controlled conditions to monitor drying processes in representative assemblies. We found a 2 m hydrostatic pressure led to a significant increase in water uptake, e.g., 20% for spruce under water for 4 days. In addition, interstitial gaps act as reservoirs and preferential water pathways. In consequence, this added water notably delays drying and heightens mould risk. The combined dataset from these experiments will improve our understanding of assemblies’ behaviour during flood events and inform flood-resilient design guidelines.

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 categoriesMeta-epidemiology (narrow)
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 score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.226
Teacher spread0.219 · 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 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
Published2025
Admission routes2
Has abstractyes

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