Implementation of a long-term monitoring approach for the operational safety of highway tunnel structures in a severely seismic area of China

Abstract

Summary With the rapid development of highway and railway transportation in China, many tunnels are constructed at the same time within the same region. It has become a challenge how to control dynamically such a large number of tunnel structures in long‐term operation and ensure their safety. In this work, we focus on the construction of common characteristics of these tunnels built during the same period in the same region. In particular, we propose a concept and a systematic component of long‐term health monitoring and develop a representative system of tunnel structure for such regional tunnels. Aiming at the engineering background, we consider the soft‐rock tunnels in the Guang‐Gan Expressway (GGE), which are located at the core of the Wenchuan earthquake zone, taking the Dujiashan Tunnel as a representative project. Based on the loading data of the secondary lining from long‐term monitoring, the fuzzy model is employed to evaluate the structure conditions for its safety. On the basis of such theoretical analysis, we therefore establish the relationships between the representative project and other soft‐rock tunnels, and then the structural safety status of the nonrepresentative project is deduced and achieved. The present study shows that the vast majority of segments of the soft‐rock tunnels on the GGE are safe. At the same time, the network transmission hardware platform and security evaluation with the alerting software system are installed successfully for those tunnels. Using the long‐term health monitoring and representative system of tunnel structure for soft‐rock tunnels at the core of the Wenchuan earthquake zone, real‐time monitoring and management of the safe status of all the soft‐rock tunnels on the GGE across the entire life cycle can be realized.

An ensemble-based change-point detection method for identifying unexpected behaviour of railway tunnel infrastructures

“…Change-point methods aim to identify the exact moment when the monitored variable of the system starts to deviate abruptly from an equilibrium level. Change-point detection algorithms are adopted in several frameworks, such as SHM and prognosis of gas turbines [Lipowsky et al, 2010;Maleki et al, 2016], variation of air pollution concentration [Carslaw et al, 2006], variation of climate parameters in order to monitor climate change characteristics [Reeves et al, 2007], failure of pipes in chemical industries [Tickle et al, 2010]. However, change-point methods are usually unable to point out the most critical change-point clearly, i.e.…”

Crack Characteristics and Safety Prediction for the Lining of a Typical Tunnel Located in a Seismic Area

“…The total length of the Expressway is 55.5 km and the tunnel accounts for almost half of the total length of the Guang-Gan Expressway. The proportion of soft rock (mainly Phyllite) along the tunnel is high, mainly distributed in Shenjiashan Tunnel, Dujiashan Tunnel, Qima Tunnel, Yangjiashan Tunnel, etc [15]. From the beginning of construction in 2009, the Guang-Gan Expressway has suffered severe large imposed deformations, collapses, lining cracks and other disasters.…”

System Identification of Tunnel Response to Ground Motion Considering a Simplified Model

“…Fortunately, such issues have recently been addressed (Bennett et al, 2010;Tondini et al, 2015;Li et al, 2016) resulting to an increase in their deployment (Dikmen, 2016;Wang et al, 2017).…”