Displacement-based back analysis of mitigating the effects of displacement loss in underground engineering

Abstract

Displacement-monitoring-based back analysis is a popular method for geomechanical parameter estimation. However, due to the delayed installation of multi-point extensometers, the monitoring curve is only a part of the overall one, leading to displacement loss. Besides, the monitoring and construction time on the monitoring curve is difficult to determine. In the literature, the final displacement was selected for the back analysis, which could induce unreliable results. In this paper, a displacement-based back analysis method to mitigate the influence of displacement loss is developed. A robust hybrid optimization algorithm is proposed as a substitute for time-consuming numerical simulation. It integrates the strengths of the nonlinear mapping and prediction capability of the support vector machine (SVM) algorithm, the global searching and optimization characteristics of the optimized particle swarm optimization (OPSO) algorithm, and the nonlinear numerical simulation capability of ABAQUS. To avoid being trapped in the local optimum and to improve the efficiency of optimization, the standard PSO algorithm is improved and is compared with other three algorithms (genetic algorithm (GA), simulated annealing (SA), and standard PSO). The results indicate the superiority of OPSO algorithm. Finally, the hybrid optimization algorithm is applied to an engineering project. The back-analyzed parameters are submitted to numerical analysis, and comparison between the calculated and monitoring displacement curve shows that this hybrid algorithm can offer a reasonable reference for geomechanical parameters estimation.

Keywords

• Rock mass
• Intelligent back analysis
• Geomechanical parameters
• Displacement loss
• Underground engineering