In recent decades, many cities have become densely populated due to increased urbanization, and the transportation infrastructure system has been heavily used. The downtime of important parts of the infrastructure, such as tunnels and bridges, seriously affects the transportation system’s efficiency. For this reason, a safe and reliable infrastructure network is necessary for the economic growth and functionality of cities. At the same time, the infrastructure is ageing in many countries, and continuous inspection and maintenance are necessary. Nowadays, detailed inspections of large infrastructure are almost exclusively performed by inspectors on site, which is both time-consuming and subject to human errors. However, the recent technological advancements in computer vision, artificial intelligence (AI), and robotics have opened up the possibilities of automated inspections. Today, semiautomatic systems such as drones and other mobile mapping systems are available to collect data and reconstruct 3D digital models of infrastructure. This significantly decreases the downtime of the infrastructure, but both damage detection and assessments of the structural condition are still manually performed, with a high impact on the efficiency and accuracy of the procedure. Ongoing research has shown that deep-learning methods, especially convolutional neural networks (CNNs) combined with other image processing techniques, can automatically detect cracks on concrete surfaces and measure their metrics (e.g., length and width). However, these techniques are still under investigation. Additionally, to use these data for automatically assessing the structure, a clear link between the metrics of the cracks and the structural condition must be established. This paper presents a review of the damage of tunnel concrete lining that is detectable with optical instruments. Thereafter, state-of-the-art autonomous tunnel inspection methods are presented with a focus on innovative mobile mapping systems for optimizing data collection. Finally, the paper presents an in-depth review of how the risk associated with cracks is assessed today in concrete tunnel lining.

Fibre-reinforced shotcrete (sprayed concrete) is one of the major components in the support system for tunnels in hard rock. Several empirical design methodologies have been developed over the years due to the complexity and many uncertainties involved in rock support design. Therefore, this paper aims to highlight how the choice of design methodology and fibre type impacts the structural capacity of the lining and the emission of greenhouse gases (GHG). The paper starts with a review of different design methods. Then, an experimental campaign is presented in which the structural performance of shotcrete reinforced with various dosages of fibres made of steel, synthetic and basalt was compared. A case study is presented in which the permanent rock support is designed based on the presented design methods. Here, only the structural requirements were considered, and suitable dosages of fibres were selected based on the experimental results. The emission of GHG was calculated for all design options based on environmental product declarations for each fibre type. The result in this paper indicates that synthetic fibres have the greatest potential to lower the emissions of GHG in the design phase. Moreover, the choice of design method has a significant impact on the required dosage of fibres.

Although the failure of a concrete dam is a complex and highly dynamic process, the current safety assessments of concrete gravity and buttress dams rely on a simplified 2D stability analysis, which neglects the load redistribution due to 3D monolith interactions and the valley shape. In addition, the estimation of breach parameters in concrete dams is based on assumptions rather than analyses, and better prediction methods are needed. Model tests have been conducted to increase the understanding of the failure behavior of concrete dams. A scale model buttress dam, with a scale of 1:15, consisting of 5 monoliths that were 1.2 m in height and 4 m in width, was constructed and loaded to failure using water pressure. The model dam had detachable abutment supports and shear keys to permit variations in the 3D behavior. The results showed that the shear transfer was large between the monoliths and that the failure of a single dam monolith is unlikely. A greater lateral restraint gives not only a higher failure load but also a better indication of impending failure. These findings suggest that the entire dam, including its boundary conditions, should be considered during a stability assessment. The results also suggest that the common assumption in dam safety codes that a single monolith fails during flooding analysis is not conservative. The dataset obtained provides a foundation for the future development of dam-monitoring alarm limits and for predictive models of dam-breaching processes.

In the assessment of concrete dams in cold climate, it is common that the theoretical stability becomes insufficient for load cases that include ice loads. However, the magnitude and return period of these ice loads have a high degree of uncertainty. This study estimates the magnitude of ice loads on eight concrete dam monoliths using measurements of their displacement from 29 winters. In the displacement signals, events are identified and assumed to be caused solely by ice loads. The observed displacement during an event is interpreted as an ice load using a load–displacement relationship derived from FE simulations of each dam. These simulations show that ice loads of the magnitudes given in design guidelines and recorded in previous measurements would significantly affect the structural response of the studied dams. However, only small traces of ice loads can be found in the observed responses of the studied dams. The estimated ice loads are significantly lower than the ice loads recorded in traditional ice load measurements. These results indicate that the average magnitude of ice load on an entire monolith is significantly lower than the measured local pressures. This would imply that ice loads may be a smaller concern regarding dam safety than previously believed.

Concrete buttress dams could potentially be susceptible to high‐frequency vibrations, especially in the cross‐stream direction, due to their slender design. Previous studies have mainly focused on low‐frequency vibrations in stream direction using a simplified foundation model with the massless method, which does not consider topographic amplifications. This paper therefore investigates the nonlinear behaviour of concrete buttress dams subjected to high‐frequency excitations, considering cross‐stream vibrations. For comparison, the effect of low‐frequency excitations is also investigated. The influence of the irregular topography of the foundation surface on the amplification of seismic waves at the foundation surface and thus in the dam is considered by a rigorous method based on the domain‐reduction method using the direct finite element method. The sensitivity of the calculated response of the dam to the free‐field modelling approach is investigated by comparing the result with analyses using an analytical method based on one‐dimensional wave propagation theory and a massless approach. Available deconvolution software is based on the one‐dimensional shear wave propagation to transform the earthquake motion from the foundation surface to the corresponding input motion at depth. Here, a new deconvolution method for both shear and pressure wave propagation is developed based on an iterative time‐domain procedure using a one‐dimensional finite element column. The examples presented showed that topographic amplifications of high‐frequency excitations have a significant impact on the response of this type of dam. Cross‐stream vibrations reduced the safety of the dam due to the opening of the joints and the increasing stresses. The foundation modelling approach had a significant impact on the calculated response of the dam. The massless method produced unreliable results, especially for high‐frequency excitations. The free‐field modelling with the analytical method led to unreliable joint openings. It is therefore recommended to use an accurate approach for foundation modelling, especially in cases where nonlinearity is considered.