Yuanli Ma
Generating prototypical residential building geometry models using a new hybrid approach
Ma, Yuanli; Deng, Wu; Xie, Jing; Heath, Tim; Xiang, Yeyu; Hong, Yuanda
Authors
Wu Deng
Jing Xie
TIMOTHY HEATH TIM.HEATH@NOTTINGHAM.AC.UK
Professor of Architecture
Yeyu Xiang
Yuanda Hong
Abstract
Building prototyping has regularly been used in building performance analyses with statistically feasible models. The novelty of this research involves a new hybrid approach combining stratified sampling and k-means clustering to establish building geometry prototypes. The research focuses on residential buildings in Ningbo, China. Seventeen small residential districts (SRDs) containing 367 residential buildings were systemically selected for survey and data collection. The stratified sampling used building construction year as the main parameter to generate stratification. Floor numbers, shape coefficients, floor areas, and window-to-wall ratios were used as the four observations for k-means clustering. Based on this new approach, nine building geometry prototypes were identified and modelled. These statistically representative prototypes provide building geometrical information and characteristic-based evaluations for subsequent building performance analysis.
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 8, 2021 |
Online Publication Date | Apr 1, 2021 |
Publication Date | Jan 1, 2022 |
Deposit Date | Apr 28, 2021 |
Publicly Available Date | Apr 2, 2022 |
Journal | Building Simulation |
Print ISSN | 1996-3599 |
Electronic ISSN | 1996-8744 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 15 |
Issue | 1 |
Pages | 17-28 |
DOI | https://doi.org/10.1007/s12273-021-0779-6 |
Keywords | Energy (miscellaneous); Building and Construction |
Public URL | https://nottingham-repository.worktribe.com/output/5500835 |
Publisher URL | https://link.springer.com/article/10.1007/s12273-021-0779-6 |
Additional Information | This is a post-peer-review, pre-copyedit version of an article published in Building Simulation. The final authenticated version is available online at: https://doi.org/10.1007/s12273-021-0779-6 |
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