Rapid exploitation of city underground space has led to the development of increasingly more underground slender-shape infrastructure like pedestrian tunnels, concourses, subway walkways, underground shopping streets, etc. Pedestrian evacuation in those public places in case of emergency can be disastrous if not properly guided. Therefore, it is important to understand how to enhance the evacuation efficiency through proper active guidance. In this study, we propose a digital twin based guiding system for pedestrian emergency evacuation inside a slender-shape infrastructure, aiming at enhancing the overall evacuation efficiency. Composition and calibration process of the guiding system are described, and a cellular automata based model is established to serve as the digital twin model. Two guidance strategies, namely traditional fixed guidance and smart guidance, are adopted by the digital twin to generate guidance instructions. A smart guidance strategy using a semi-empirical approach is proposed based on the understanding of the free movement and congested movement of pedestrian flow. Systems under different guiding strategies are compared and discussed over their effectiveness to promote excavation efficiency in different pedestrian population distribution settings. The simulation results show that a system under smart guidance tends to have shorter evacuation time (up to 23.8% time saving) and performs with more stability for pedestrian evacuations over the traditional fixed guided systems. The study provides insight for potential real applications of a similar kind.

Long term performance of urban metro tunnels requires that the tunnel structure maintains not only a sound structural state, i.e., free from significant damages, but also a minimal change in the physical shape. Over-deformation can cause structural damage but more importantly can affect the safe operation of the metro lines, therefore is a primary target of monitoring and intervention where it becomes necessary. This paper presents an overview of recent developments in field monitoring and assessment of metro tunnels in soft soil concerning over-deformation. In particular, the over-deformation of shield tunnel rings due to nearby construction activities, especially deep excavation, and its rectification using grout treatment is discussed on the basis of relevant field experiment and numerical modelling reported in recent publications. Key considerations in the development of a Material Point Method (MPM) based numerical modelling framework for simulating explicitly the grouting operations are highlighted, and the general performance of the numerical model is examined with reference to the field test data and characteristic parametric observations. Further research needs in terms of more rigorous assessment and design of grouting treatment, in conjunction with the continued development of numerical modelling capabilities, are discussed.

Underground grain silos offer advantages such as space efficiency, low energy consumption, and concealment, but their long-term exposure to complex geotechnical environments makes them vulnerable to concealed, multimode, and spatially distributed water leakage. To address the limitations of existing detection and monitoring methods, this study proposes a frequency-modulated actively heated fiber-optic sensing method for distributed water leakage monitoring in underground grain silos. Based on transient heat conduction theory, a one-dimensional finite element heat transfer model and a parametric numerical simulation framework were developed to investigate the effects of infiltrated water thickness, heating power, and excitation duration on temperature responses. A sensing indicator system and evaluation framework were then established to enable multimode leakage identification and quantitative assessment of leakage parameters, including leakage amount, grain moisture content, and moist layer thickness. Laboratory model tests under 12 leakage conditions verified the effectiveness of the proposed method. The leakage mode identification accuracy reached 100%, and the experimental indicators showed good agreement with the optimal excitation curves, with R² values greater than 0.963. The inverted grain moisture content errors were within 1% for all conditions, and the moist layer thickness errors were less than 1 mm in 11 conditions, with a maximum error of 1.56 mm. These results demonstrate that the proposed method provides an effective technical approach for accurate identification and assessment of concealed multimode leakage in underground grain silos.