Abstract
The stability of tunnels has mainly been evaluated based on displacement. Because displacement due to the excavation process is significant, back analysis of the structure and ground can be performed easily. Recently, the length of a segment‐lined tunnel driven by the mechanized tunneling method is increasing. Because the internal displacement of a segment‐lined tunnel is trivial, it is difficult to analyze the stability of segment‐lined tunnels using the conventional method. This paper proposes a back analysis method using stress and displacement information for a segment‐lined tunnel. A differential evolution algorithm was adopted for tunnel back analysis. Back analysis based on the differential evolution algorithm using stress and displacement was established and performed using the finite difference code, FLAC3D, and built‐in FISH language. Detailed flowcharts of back analysis based on DEA using both monitored displacement stresses were also suggested. As a preliminary study, the target variables of the back analysis adopted in this study were the elastic modulus, cohesion, and friction angle of the ground. The back analysis based on the monitored displacement is useful when the displacement is significant due to excavation. However, the conventional displacement‐based back analysis is unsuitable for a segment‐lined tunnel after construction because of its trivial internal displacement since the average error is greater than 32% and the evolutionary calculation is finalized due to the maximum iteration criteria. The average error obtained from the proposed back analysis algorithm using both stress and displacement ranged within approximately 6–8%. This also confirms that the proposed back analysis algorithm is suitable for a segment‐lined tunnel.
Highlights
Revisit to Differential Evolution AlgorithmDifferential Evolution Analysis (DEA) was developed to optimize the nonlinear and nondifferentiable in the continuous space function (Hwang [12])
The error of cohesion is not sensitive to the boundary conditions, it is improved greatly compared to the result obtained from Table 5 with the displacement-based back analysis. e estimated average error ranged approximately 6–8%, which suggests that the error can be reduced dramatically with the
Because the internal displacement of a segment-lined tunnel is trivial, it is difficult to analyze the stability of a segment-lined tunnel using the conventional method
Summary
Differential Evolution Analysis (DEA) was developed to optimize the nonlinear and nondifferentiable in the continuous space function (Hwang [12]). DEA is a searching algorithm that uses the target variable vector of the population size. DEA has the same basic operations as EA, which include generating an initial population randomly and extracting the outstanding objects through mutation, crossover, and selection stage. DEA uses operations, such as mutation, crossover, and selection, which are similar to the Genetic Algorithm (GA). XNP,G] in a population, a new generation vector can be expressed as equation (1). E target vector (xi,G+1) is compared with the trial vector (ui,G+1); good object traits are selected for the generations. ⎧⎨ ui,G+1, ⎩ xi,G, if fui,G+1 ≤ fxi,G, otherwise As it is reviewed, back analysis based on the monitored displacement is useful when the displacement is significant due to excavation. The internal displacement of a segment-lined tunnel after the construction is trivial so that the application of conventional displacement-based back analysis is unsuitable. us, the conventional DEA using the monitored displacement is modified to consider the monitored stress information as well as the displacement to enhance the convergence in this study. e error function should be revised to accommodate the different observation variables
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