TY - JOUR
T1 - Holistic clash detection improvement using a component dependent network in BIM projects
AU - Hu, Yuqing
AU - Castro-Lacouture, Daniel
AU - Eastman, Charles M.
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/9
Y1 - 2019/9
N2 - Building information modeling (BIM) has been increasingly used for design coordination, and clash detection is one important application. However, some studies argued that BIM-enabled clash detection contains many irrelevant clashes. This paper proposes to use network analysis to improve clash detection from a holistic view because a building is an inseparable whole and the dependency relations between building components influence the impacts of clashes. A building component network centered on clash objects is built to represent component dependency. To build the network, this paper determines three kinds of spatial dependent: clash, impact, and connection. For clash relations, the paper further distinguishes four types: intersection, penetration, penetration through, and containment based on the intersection curves of clash objects. To improve generality, Industry Foundation Classes (IFC) models are used to query geometric information and bounding volume hierarchy (BVH) structures are used to eliminate irrelevant comparison for expediting the query process. The paper tests the network method on a real project for improving clash detection and confirms that the method helps to identify irrelevant clashes in four scenarios and reduces 17% of irrelevant clashes. In addition, the paper uses the network to automatically group relevant clashes, thereby decreasing >50% of the clashes initially reported. The paper also shows the function of the component dependent network to analyze the surrounding environment of clashes and identify central components for supporting clash correction.
AB - Building information modeling (BIM) has been increasingly used for design coordination, and clash detection is one important application. However, some studies argued that BIM-enabled clash detection contains many irrelevant clashes. This paper proposes to use network analysis to improve clash detection from a holistic view because a building is an inseparable whole and the dependency relations between building components influence the impacts of clashes. A building component network centered on clash objects is built to represent component dependency. To build the network, this paper determines three kinds of spatial dependent: clash, impact, and connection. For clash relations, the paper further distinguishes four types: intersection, penetration, penetration through, and containment based on the intersection curves of clash objects. To improve generality, Industry Foundation Classes (IFC) models are used to query geometric information and bounding volume hierarchy (BVH) structures are used to eliminate irrelevant comparison for expediting the query process. The paper tests the network method on a real project for improving clash detection and confirms that the method helps to identify irrelevant clashes in four scenarios and reduces 17% of irrelevant clashes. In addition, the paper uses the network to automatically group relevant clashes, thereby decreasing >50% of the clashes initially reported. The paper also shows the function of the component dependent network to analyze the surrounding environment of clashes and identify central components for supporting clash correction.
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U2 - 10.1016/j.autcon.2019.102832
DO - 10.1016/j.autcon.2019.102832
M3 - Article
AN - SCOPUS:85066126302
SN - 0926-5805
VL - 105
JO - Automation in Construction
JF - Automation in Construction
M1 - 102832
ER -