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Building Simulation 2018, 11(2): 281-292 https://doi.org/10.1007/s12273-017-0412-x
Research Article | Issue | Published: 03 October 2017

A graph- and feature-based building space recognition algorithm for performance simulation in the early design stage

Show Author's Information Hongzhong Chen1,2,  Ziwei Li1,2,  Xiran Wang3,  Borong Lin1,2( )
Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
Department of Architecture, School of Architecture, Tsinghua University, Beijing 100084, China
Keywords:
model recognition, early design stage, performance-oriented design, graph- and feature-based method
Cite this article:
Chen H, Li Z, Wang X, et al. A graph- and feature-based building space recognition algorithm for performance simulation in the early design stage. Building Simulation, 2018, 11(2): 281-292. https://doi.org/10.1007/s12273-017-0412-x
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Abstract Full text About this article

This paper presents a graph- and feature-based building space recognition algorithm for a boundary representation format (B-rep) geometric model, which can identify the building element type and space. The flow of the algorithm is described in detail, including the construction of a building geometric topology relation graph (BTG), the recognition of building element type, and the extraction of building space based on graph and local feature. The algorithm can be applied to the design of a building scheme; it can quickly identify and transform the geometric model into the input model required by the performance simulation software. This is a key step in realizing a performance-oriented design in the early design stage. We implemented this algorithm using SketchUp for testing its performance. Through the case study, it is proved that the algorithm can recognize the model and extract all the building spaces accurately. There is linear correlation between the recognition time and number of faces. Moreover, at the time of analysis, a model composed of 500 spaces and 3001 faces did not exceed 1.69 s, which meets the requirements of most applications well. Compared to previous works, this algorithm performs well in both recognition accuracy and time efficiency simultaneously, and can better serve the actual demand of automatic real-time building performance feedback in the early design stage. Finally, the future work regarding performance-oriented design based on model recognition is proposed.


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About this article

A graph- and feature-based building space recognition algorithm for performance simulation in the early design stage

Show Author's information Hongzhong Chen1,2, Ziwei Li1,2, Xiran Wang3, Borong Lin1,2( )
Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
Department of Architecture, School of Architecture, Tsinghua University, Beijing 100084, China

Abstract

This paper presents a graph- and feature-based building space recognition algorithm for a boundary representation format (B-rep) geometric model, which can identify the building element type and space. The flow of the algorithm is described in detail, including the construction of a building geometric topology relation graph (BTG), the recognition of building element type, and the extraction of building space based on graph and local feature. The algorithm can be applied to the design of a building scheme; it can quickly identify and transform the geometric model into the input model required by the performance simulation software. This is a key step in realizing a performance-oriented design in the early design stage. We implemented this algorithm using SketchUp for testing its performance. Through the case study, it is proved that the algorithm can recognize the model and extract all the building spaces accurately. There is linear correlation between the recognition time and number of faces. Moreover, at the time of analysis, a model composed of 500 spaces and 3001 faces did not exceed 1.69 s, which meets the requirements of most applications well. Compared to previous works, this algorithm performs well in both recognition accuracy and time efficiency simultaneously, and can better serve the actual demand of automatic real-time building performance feedback in the early design stage. Finally, the future work regarding performance-oriented design based on model recognition is proposed.

Keywords: model recognition, early design stage, performance-oriented design, graph- and feature-based method

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Publication history
Copyright
Acknowledgements

Publication history

Received: 12 May 2017
Revised: 20 July 2017
Accepted: 15 August 2017
Published: 03 October 2017
Issue date: April 2018

Copyright

© Tsinghua University Press and Springer-Verlag GmbH Germany 2017

Acknowledgements

This research is supported by China National 13th Five-year Science and Technology Support Project (2016YFC0700209) and "Total Performance of Low Carbon Buildings in China and the UK" project which is provided by the National Natural Science Foundation of China (51561135001).

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