An evaluation of architects' readiness for conducting energy modelling using BIM tools to achieve high energy performance buildings in the UK and Canada
Bibliographic record
Abstract
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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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 | 0.001 | 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".