Digital twin (DT), serving as a powerful tool for reflecting semantic and complex properties of underground infrastructure, plays a crucial role in optimising decision-making and closing sensing-control loop. Its application has demonstrated promising potential in advancing project quality and construction efficiency. Nevertheless, the absence of a maturity model (MM) limits the comprehension, evaluation, advancement, and implementation of DT. A quantitative MM further provides insights and benchmarks for technological advancement and functional completeness. The study firstly proposes a five-level maturity hierarchy based on systematic literature review and specialities of underground infrastructure. A qualitative evaluation system is constructed comprising 5 dimensions and 13 rubrics. Considering the interdependencies among rubrics, a D-ANP (Decision-Making Trial and Evaluation Laboratory & Analytical Network Process) method is utilized to evaluate the maturity level and assign weights to rubrics. Effectiveness and feasibility of the proposed MM are demonstrated through case studies involving subway station and tunnel DTs. The results indicate that the MM provides valuable perspectives and enables cross-disciplinary and multi-phase comparisons of DTs from the technological perspective.

中文翻译：

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基于D-ANP的地下基础设施定量数字孪生成熟度模型

数字孪生（DT）作为反映地下基础设施语义和复杂属性的有力工具，在优化决策和闭环传感控制方面发挥着至关重要的作用。其应用在提高工程质量和施工效率方面展现出了巨大的潜力。然而，成熟度模型（MM）的缺乏限制了DT的理解、评估、推进和实施。定量 MM 进一步提供了技术进步和功能完整性的见解和基准。该研究首先基于系统文献综述和地下基础设施的专业性提出了五级成熟度等级。构建了包含 5 个维度、13 个评分标准的定性评价体系。考虑到评价标准之间的相互依赖性，采用D-ANP（决策试验和评估实验室及分析网络过程）方法来评估评价标准的成熟度并为评价标准分配权重。通过涉及地铁车站和隧道 DT 的案例研究证明了所提出的 MM 的有效性和可行性。结果表明，MM提供了有价值的视角，并能够从技术角度对DT进行跨学科和多阶段的比较。