Advancements in digital twin modeling for underground spaces and lightweight geometric modeling technologies

The construction of a twin model with high fidelity, real-time mapping and scalability is the foundation for realizing digital twin in underground space. Given the large size and complexity of digital twin geometric model data in underground space, it is of practical significance to study lightweigh...

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Veröffentlicht in:Automation in construction 2024-09, Vol.165, p.105578, Article 105578
Hauptverfasser: Gong, Haofeng, Su, Dong, Zeng, Shiqi, Chen, Xiangsheng
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Sprache:eng
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Zusammenfassung:The construction of a twin model with high fidelity, real-time mapping and scalability is the foundation for realizing digital twin in underground space. Given the large size and complexity of digital twin geometric model data in underground space, it is of practical significance to study lightweighting techniques to speed up transmission and enhance rendering performance. Therefore, this paper provides a comprehensive review of current research on digital twin modeling of underground space, aiming to clarify the elements, methods, and technical directions for constructing the twin model. Firstly, the conceptual framework of digital twin modeling in underground space is proposed and the components of virtual model are elaborated in detail. Current modeling methods and tools for geological bodies, machines and structural bodies are reviewed. Finally, existing lightweighting methods for geometric modeling and their advantages and disadvantages are summarized, and future research directions for digital twin modeling and lightweighting methods are proposed. [Display omitted] •A systematic review on digital twin of underground space research is provided.•Digital twin framework for underground space is proposed.•The advantages and limitations of different modeling methods are analyzed.•A review of existing modeling lightweighting techniques is provided.•Future research directions on lightweighting technology are proposed.
ISSN:0926-5805
DOI:10.1016/j.autcon.2024.105578