A quantitative digital twin maturity model for underground infrastructure based on D-ANP

Abstract

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.