Knowledge‐guided digital twin modeling method of generating hierarchical scenes for a high‐speed railway Article Swipe
Heng Zhang
,
Wen Zhao
,
Zujie Han
,
Jun Zhu
,
Qing Zhu
,
Xu Zhu
,
Dejun Feng
,
Yongjun Song
,
Shufeng Song
,
Bo Zhang
,
Fengpin Jia
,
Yakun Xie
,
Yushan Quan
,
Junhu Zhang
,
Weilian Li
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1111/tgis.13110
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1111/tgis.13110
China's railway construction is rapidly transitioning toward integrated management of “stakeholders, management elements, and management processes”. Therefore, comprehensive and whole‐process digital twin scene modeling is urgently needed for intelligent railway construction. However, the requirements of three‐dimensional scenes in different stages vary hierarchically, resulting in a lack of construction semantics and limited universality in modeling. This article proposes a knowledge‐guided digital twin modeling method of hierarchical scenes for a high‐speed railway. We first build a knowledge graph of “knowledge‐model‐data” to achieve an accurate and hierarchical description of railway scenes. We then establish a parameter‐driven modeling method that integrates knowledge guidance and primitive combination to generate a display scene and a virtual design scene automatically. Third, we propose joint linkage and model growth methods for construction action modeling, which are used to generate a virtual construction scene. Finally, in response to the hierarchical scene‐generating requirements in different stages, we conduct intelligent modeling experiments for the entire design and construction process. The knowledge graph of the hierarchical semantic description mode significantly improves the flexibility and universality of the modeling method. The proposed modeling method for the entire process contributes to the rapid representation of design data, in‐depth design, visual exploration, and dynamic optimization of the construction process. This article provides a reliable digital twin modeling solution for the entire process to improve design and construction quality.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/tgis.13110
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/tgis.13110
- OA Status
- bronze
- Cited By
- 4
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387820982
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4387820982Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1111/tgis.13110Digital Object Identifier
- Title
-
Knowledge‐guided digital twin modeling method of generating hierarchical scenes for a high‐speed railwayWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-10-20Full publication date if available
- Authors
-
Heng Zhang, Wen Zhao, Zujie Han, Jun Zhu, Qing Zhu, Xu Zhu, Dejun Feng, Yongjun Song, Shufeng Song, Bo Zhang, Fengpin Jia, Yakun Xie, Yushan Quan, Junhu Zhang, Weilian LiList of authors in order
- Landing page
-
https://doi.org/10.1111/tgis.13110Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/tgis.13110Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/tgis.13110Direct OA link when available
- Concepts
-
Computer science, Process (computing), Visual modeling, Artificial intelligence, Graph, Knowledge modeling, Domain knowledge, Theoretical computer science, Unified Modeling Language, Programming language, Operating system, SoftwareTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4Per-year citation counts (last 5 years)
- References (count)
-
47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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