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Enregistrement W7162761591 · doi:10.4224/40004053

Guideline on assessing the effects of climate change on the resilience to moisture-related degradation of building envelopes

2024· report· en· W7162761591 sur OpenAlexaffvenue
Lin Wang, Zhe Xiao, Maurice Defo, M A Lacasse

Notice bibliographique

RevueNPARC · 2024
Typereport
Langueen
Domaine
Thématique
Établissements canadiensNational Research Council Canada
Organismes subventionnairesnon disponible
Mots-clésBuilding envelopeResilience (materials science)Climate changeBuilding designHazardous wasteEnvelope (radar)Overheating (electricity)Risk assessment

Résumé

récupéré en direct d'OpenAlex

Climate change is bringing more frequent and severe weather events, along with an overall trend toward more intensive environmental loads acting on buildings, such as higher temperatures and wind-driven rain. The increase in environmental loads poses a hazardous trend for building envelope systems, whose function is to separate indoor and outdoor environments, because these higher loads are likely to introduce a greater risk of moisture-related deterioration of building envelope components over their service life, as well as a higher risk of indoor overheating during summertime heat waves. As defined by the IPCC, climate resilience is the “capacity of social, economic and ecosystems to cope with a hazardous event or trend or disturbance.” For building envelope systems, design activities need to take this hazardous trend—the increase in environmental loads—into consideration in order to help ensure climate resilience against: (1) moisture-related deterioration of building envelope components; and (2) heat-wave-induced indoor overheating. This document focuses on the first aspect of climate resilience of building envelopes, which essentially refers to the moisture performance of building envelopes subjected to changing climates. It provides guidance on the use of a stochastic approach to assess whether building envelope systems are sufficiently resilient to withstand moisture-related consequences resulting from the effects of climate change. Hygrothermal simulation is generally used to assess the heat and moisture transport behaviours in building envelope systems and to predict moisture-related deterioration of building envelope components. Lacasse et al. (2018) developed a guideline on the design for durability of building envelopes using hygrothermal models to provide results from which to infer the durability performance of building envelope systems. In that guideline, high-level guidance was provided on the procedure for durability performance evaluation, either for short-term comparative studies among different building envelope systems under different climate change scenarios or for long-term service life assessment of a specific building envelope system under a specific climatological period. This guideline provides more detailed information on short-term comparative studies while considering uncertainties in input parameters, such as future climate data, boundary conditions, and building material properties. These uncertainties arise from the process of preparing the input information and can be categorized as systematic uncertainty and random uncertainty. For example, future climate data can be generated from different meteorological models, and the uncertainty caused by differences among these models can be considered systematic uncertainty. On the other hand, for a given meteorological model, there is always unknown information required to feed the model, such as the initial conditions for meteorological modelling, and this uncertainty can be considered random uncertainty. In addition, with the progression of climate change and uncertain human responses to climate change, the input information is subject to variation. For example, boundary conditions are influenced by microclimate conditions, which are highly affected by changes in local landscapes. Building material components are also subject to aging due to more frequent extreme weather events and more intensive environmental loads, and material property values may deviate from originally expected values as a result of the aging process. All of these uncertainties influence the reliability of using deterministic hygrothermal simulations to assess the climate resilience of building envelopes. Therefore, a stochastic approach should be used to account for all uncertainties in order to obtain probabilistic simulation results that can be used to assess the risk of moisture-related deterioration and to develop effective design or mitigation solutions that improve climate resilience against moisture deterioration. The information provided in this document describes the procedure used for hygrothermal performance analysis and probabilistic risk assessment of moisture-related deterioration in building envelope systems using stochastic simulation. It is intended for use by expert practitioners who have knowledge of hygrothermal simulation and require hygrothermal performance results to assess climate-resilient building envelope design or retrofit while considering uncertainties in input parameters. Given that stochastic simulations require extensive computational resources and advanced programming skills, which are not widely available in the building design or simulation industry, this document also provides a case study comparing stochastic and deterministic simulation results to help practitioners understand the confidence level associated with using a deterministic approach to assess the climate resilience of building envelopes. The results of this study indicate that stochastic simulation incorporates much more information than deterministic simulation and provides a more robust assessment of the risk of moisture-related degradation in wall assemblies. A sensitivity analysis showed that reducing wind-driven rain and increasing cladding ventilation rates are two important design strategies for mitigating the risk of moisture-related degradation in the envelope, as these two strategies have relatively high sensitivity indices and can significantly reduce the mould growth index, even in the presence of other uncertainties.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,021
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,044
Score d'incertitude au seuil0,088

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,021
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,001
Communication savante0,0030,003
Science ouverte0,0060,002
Intégrité de la recherche0,0050,004
Charge utile insuffisante (le modèle a refusé de juger)0,0240,021

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,046
Tête enseignante GPT0,360
Écart entre enseignants0,314 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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