An evaluation of architects' readiness for conducting energy modelling using BIM tools to achieve high energy performance buildings in the UK and Canada
Notice bibliographique
Résumé
Buildings, consume more than 30% of the world's energy and is the world's largest energy \nconsuming sector, contributing nearly a quarter of the total global greenhouse gas emissions. \nGlobal warming is the result of emission of greenhouse gases, and this represents a significant \nexistential crisis. The effective design of buildings is one way to mitigate this issue and this \nstarts with the design of the building. One of the architect's main responsibilities is the \nbuilding’s geometric design, which has a considerable impact on energy consumption. \nBuilding Performance Analysis (BPA) is generally conducted during the later design stages \noften in support of the mechanical and electrical design, such as heating and cooling systems. \nTo achieve a High Energy Performance Building (HEPB), this research considers the \npotential impact and implementation of a process which might bring the geometric design \nstage and energy analysis stages closer to each other. While architects usually deal with \ngeometrical design, much of energy performance analysis work is carried out by consultant \nenergy specialists. However, new BIM tools have the potential to make this stage of analysis \nmore accessible to architects, who may not have specific building physics knowledge. \nThe purpose of this study is to assess the acceptability of BIM based energy analysis tools to \narchitects and assess their potential use in early stage energy analysis undertaken by nonspecialist architects. The aim of this research is to evaluate the conditions of the design \nprocess for HEPB in the UK and Canada and develop a series of recommendations to better \nenable architects to address energy efficiency in the early stages of the design process by \nusing BIM tools. \nAn abductive research approach is used to test existing theories regarding the ability of BIM \nto design and analyse green buildings. The survey of UK and Canadian architects identifies \nissues such as; standards, underlying knowledge, client demand and the use of BIM tools to \nidentify applicability of the approach. The results from the study are used to understand the \nprocesses of HEPBs architectural design, including the sources and tools which are used. The \nrespondents’ familiarity with BIM, its tools and ability for doing tasks in the design and \nconstruction industry, specifically regarding HEPBs design and the potential barriers for \nemploying BIM are also considered. \nThe recognised gap in the knowledge is to develop a better understanding of the issues of the \ndetachment of architects as first designers of buildings involved in geometrical design from \nthe later stages (Building Performance Analysis) and the possible solutions that might be \nprovided by BIM tools. The contribution to knowledge of the research focuses around a better \nunderstanding of the specific barriers for the implementation and use of BIM energy analysis \ntools by architectural practices which will be achieved through finding weaknesses in the \ncurrent process of design process and discovering potential solutions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,003 |
| Communication savante | 0,006 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».