Civil and Environmental Engineering - Conference Items
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Item Time-dependent performance of Dublin Port Tunnel(Civil Engineering Research Association of Ireland, 2020-08) Wang, Chao; Friedman, Miles; Li, Zili; Science Foundation Ireland; Transport Infrastructure IrelandIt is widely observed that existing tunnels deform and deteriorate over time due to various factors. Among them, tunnel lining permeability plays a significant role. In practice, the development of lining cracks and adjustment of drainage system may gradually alter the permeability of tunnel lining and water drainage path around a tunnel with time. Nevertheless, past investigations usually assume unchanged lining permeability during the whole life of a tunnel but fail to take time-dependent aging process into consideration. In this study, a set of hydro-mechanical coupled analyses is conducted to evaluate the effect of time-dependent crack development on the behaviour of a cross passage twin-tunnel section in Dublin Port Tunnel. The numerical results compare the transverse and longitudinal settlement profiles above the twin-tunnel with and without cross passage. The deformational characteristics of tunnel lining subject to the influence of the time-dependent permeability change are also analysed, which brings more insights into the understanding of aging tunnel structures.Item Hydraulic permeability and ageing behaviour of Dublin Port Tunnel(International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE), 2022-05) Wang, Chao; Li, Zili; Friedman, Miles; Science Foundation Ireland; Transport Infrastructure IrelandTunnel hydraulic deterioration has been widely reported and investigated in many past studies where, nevertheless, the tunnel lining permeability was assumed as constant and the time-dependent hydraulic degradation process was neglected. To investigate the hydraulic ageing behaviour of Dublin Port Tunnel, in this paper, a modified ground-lining relative permeability analytical model was derived and current deteriorated lining permeability was estimated using field monitoring water flow data. Compared with the initial watertight status of Dublin Port Tunnel, the current hydraulic state of the tunnel was found to be partially permeable after more than a decade’s operation. The results from numerical simulations showed that the assumption of a constant hydraulic permeability during the lifetime of tunnel structures may not evaluate the ageing tunnel deformational performance process realistically. It is important to consider the effect of time-dependent hydraulic deterioration process on tunnel performance.Item Data extraction of tunnel point clouds from images captured by robotic camera(2024) Zhang, Ran; Li, Zili; China Scholarship CouncilThe inspection and maintenance of underground tunnels are critical to ensuring their long-term safety and stability, as well as to preventing potential accidents and costly repairs. In recent years, there has been increasing interest in the use of automated tunnel inspection systems to monitor tunnel conditions and detect any signs of deterioration. These systems, developed under projects like ROBO-SPECT [1], represent a significant advancement over traditional inspection methods such as LIDAR detection and handheld camera photography. Unlike these traditional methods, a robot-mounted HD camera offers a more efficient and effective solution for acquiring high-quality image-based data for tunnel inspection[2]. By mounting an HD camera on a robotic platform, it is possible to obtain a detailed and accurate 3D model of the tunnel environment, which can be used for further analysis and inspection. Moreover, the integration of cross-disciplinary datasets, particularly in the areas of geometry analysis and machine learning-based data extraction, is continuing to improve the accuracy and efficiency of automated tunnel inspection systems [3]. By leveraging the latest advances in machine learning and data analysis techniques [4], it is possible to extract valuable insights from the collected data, such as the identification of cracks, spalls, and other forms of tunnel deterioration. In summary, the use of robot-mounted HD cameras and cross-disciplinary data analysis techniques offers exciting opportunities for advancing the field of automated tunnel inspection. By continuing to innovate and improve these technologies, we can help ensure the long-term safety and sustainability of underground tunnel infrastructure.Item Automatic UAV surface inspection method for underground infrastructure - a case study of Dublin Port Tunnel(2023) Zhang, Ran; Li, Zili; China Scholarship CouncilThis paper proposes an automatic data acquisition method for automated UAV inspection in a complex underground road tunnel without a global navigation satellite system (GNSS) signal. The gathered image data is then processed to create a 3D reconstruction of the road tunnel for structural condition assessment.Item UAV data acquisition method for transportation tunnel inspection(2023) Zhang, Ran; Li, Zili; China Scholarship CouncilIn a large-scale underground transportation network, miles of tunnel linings require regular inspection and assessment. In civil / geotechnical industry, common routine tunnel maintenance still highly relies on labour-intensive visual inspection, manual data acquisition and subjective assessment, which leads to significant cost for a large-scale tunnel network over many miles. In this paper, the tunnel surface texture is acquired using a commercial DJI Mavic2 UAV customized by DJI MSDK automation. Due to limited GPS signal in an underground tunnel, optical flow method is used for localization. In railroad tunnels without a priori maps, the adaptive flight procedure allows the UAV to determine the tunnel axial direction and adjust the UAV orientation and position relative to the tunnel in real time. Compared to manual acquisition and manual control, the UAV automatic data acquisition procedure allow a larger inspection scope, it has higher stability and greater efficiency at a lower cost, and can create a 3D visual model of the entire tunnel in the simple geometry of railway tunnels. Compared to more sophisticated programs, the light-weight platform can be easily compiled on any DJI Mavic 2 model with low computation power and adapt to similar underground environments without the need of pretrained datasets. In future studies, the obtained tunnel images can be used to train convolution neural networks (CNN) for automatic cracks & leakage detection and tunnel condition assessment.