In recent years, the growing demand for underground infrastructure has driven expansion into larger and deeper regions. The excavation of structures under mixed ground conditions combines the dual complex challenges of soil and rock layers, such as the interaction between the depth of soil and rock layers and the depth of structural excavation, and the problem of spatial asymmetric three-dimensional beddings. While numerical simulations effectively represent ground characteristics during excavation and the interaction with support structures, the continual influx of project data frequently requires labour-intensive, repetitive design adjustments and model re-assessments. Compounded by platform interoperability issues across design, analysis, and decision-making stages. Thus, employing building information modelling (BIM) to facilitate seamless information exchange across diverse software systems can enhance workflow efficiency and improve the optimisation of engineering designs. This paper introduces a modular automated framework that combines parametric modelling and numerical simulation tools with digital platforms. By modularising and automating the design, analysis, and decision-making stages, it simplifies information exchange between digital models and numerical analysis, while enabling real-time, adaptive decision-making. Further, it integrates data from numerical simulations, historical observations, and monitoring data into digital platforms at the decision-making stage, providing dynamic criteria to adapt designs that accommodate long-term geotechnical uncertainties. Additionally, the framework emphasises the advantages of incorporating long-term local and satellite monitoring data, thereby enhancing both data management and decision-making processes. Illustrated through a workflow use case at a cut and cover excavation, sensitivity analysis identifies key parameters affecting stability under mixed ground conditions, demonstrating the framework’s capability to address complex challenges effectively. This framework ensures a continuous information flow from design through to decision-making, providing an advantage in managing ground-structure interactions.

中文翻译：

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用于混合地质条件下明挖回填开挖的模块化自动化建模框架


近年来，对地下基础设施的需求不断增长，这推动了向更大、更深的区域扩张。混合地基条件下的结构开挖结合了土层和岩层的双重复杂挑战，如土岩层深度与结构基坑深度的相互作用，以及空间不对称三维层理问题。虽然数值模拟有效地代表了开挖过程中的地层特征以及与支撑结构的相互作用，但不断涌入的项目数据经常需要劳动密集型、重复的设计调整和模型重新评估。设计、分析和决策阶段的平台互作性问题使情况更加复杂。因此，采用建筑信息模型 （BIM） 来促进不同软件系统之间的无缝信息交换，可以提高工作流程效率并改善工程设计的优化。本文介绍了一个模块化的自动化框架，它将参数建模和数值仿真工具与数字平台相结合。通过对设计、分析和决策阶段进行模块化和自动化，它简化了数字模型和数值分析之间的信息交换，同时实现了实时的自适应决策。此外，它还在决策阶段将来自数值模拟、历史观测和监测数据的数据集成到数字平台中，为适应长期岩土工程不确定性的设计提供动态标准。此外，该框架强调了整合长期本地和卫星监测数据的优势，从而加强数据管理和决策过程。 通过明挖回挖的工作流程用例，敏感性分析确定了在混合地层条件下影响稳定性的关键参数，展示了该框架有效应对复杂挑战的能力。该框架确保了从设计到决策的持续信息流，在管理地面结构交互方面提供了优势。