Automated design framework for excavation retaining structures: Extending IFC standards and integrating BIM with geotechnical simulation

Abstract

Challenges arise in automate design with building information modeling (BIM) in underground space. Industry foundation classes (IFC) standard lacks detailed entity objects for describing excavation retaining structures and geological information, and automated design based on BIM models is not yet for practical application. This study presents a novel automated framework. It integrates the extended IFC standard with mechanical analysis and BIM modeling, significantly advancing structural optimization and rebar detailing. Direct 3D model generation streamlines complex excavation projects, aligning with the trend towards automated, precision-driven design. Key contributions include: (1) the extension of the IFC standard to support excavation retaining structures with objects like IfcBracedPit and IfcPitWall, improving interoperability between geotechnical models and BIM systems; (2) the integration of heuristic algorithms for automated optimization of deformation control parameters, reducing manual intervention; and (3) the promotion of design methodology that bypasses two-dimensional modeling and directly generates three-dimensional models, enhancing efficiency and allowing engineers to focus on high-level decision-making. However, the framework is primarily suited for standard cross-section projects like subway stations and tunnels. Future work will focus on refining the framework for more complex geotechnical projects, addressing software independence and improving design robustness and independence.

Keywords

Automated building information model framework / Automatic foundation pit design / Deformation control / Automatic reinforcement detailing / Underground engineering automation

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Qiwei Wan: Project administration, Conceptualization, Writing - review & editing, Software, Methodology, Writing - original draft. Yuyuan Zhu: Writing - review & editing, Formal analysis, Validation, Data curation. Haibin Ding: Software, Writing - review & editing, Investigation, Data curation. Wentao Hu: Writing - review & editing, Formal analysis, Validation. Changjie Xu: Supervision, Writing - review & editing, Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the National Key R&D Program of China (Grant No. 2023YFC3009400), National Natural Science Foundation of China (Grant Nos. 52238009, 52208344, and 52278350), Natural Science Foundation of Jiangxi Province (Grant No. 20223BBG71018), and the Innovation Fund of Jiangxi Province for Postgraduate (Grant No. YC2024-B196).

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