Research on Automatic Parametric Modeling of Railway Bridges Based on BIM Technology
- DOI
- 10.2991/978-94-6239-682-1_13How to use a DOI?
- Keywords
- High-speed railway bridge; Building Information Modeling (BIM); Automatic modeling; Parameterization; Intelligent Construction
- Abstract
Applying BIM technology to the design of high-speed railway bridge is of great significance for improving the efficiency and quality of bridge design. In order to achieve a fully diversified bridge model construction based on design It is necessary to automatically extract key parameter information for bridge modeling from the design drawings. Taking into full consideration the constraints and correlation relationships between various parameters, a bridge component model library was established using BIM secondary development technology. Multi-parameter control of bridge component model shape. The application examples show that the method proposed in this article can provide a solution for the three-dimensional automation and intelligent modeling from two-dimensional design schemes for high-speed railway bridges.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Wanqi Wang AU - Ze Guo AU - Liu Bao AU - Xing Yang AU - Ruichang Shi PY - 2026 DA - 2026/06/30 TI - Research on Automatic Parametric Modeling of Railway Bridges Based on BIM Technology BT - Proceedings of the 2025 7th International Conference on Civil Architecture and Urban Engineering (ICCAUE 2025) PB - Atlantis Press SP - 126 EP - 132 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6239-682-1_13 DO - 10.2991/978-94-6239-682-1_13 ID - Wang2026 ER -