Abstract
With the continuous popularization and development of highway traffic in mountainous areas, the number of rock slopes is also increasing. In order to improve the stability of rock slope and reduce the harm caused by slope slip, this paper carries out numerical simulation of rock slope sliding based on particle swarm optimization algorithm. Firstly, this paper combines the differential evolution algorithm and simplex method to improve the global and local search ability of particle swarm optimization (PSO) algorithm and analyzes the performance of the algorithm. ABAQUS software is used to simulate rock slope sliding, the finite element method is used to analyze the stability of rock slope, and LS-DYNA program is used to simulate rockfall impact rock slope. During the numerical simulation, the improved algorithm is used to analyze all the data. Experimental data show that the improved PSO algorithm converges after nearly 100 iterations and the convergence speed and optimization accuracy are high. In the numerical simulation, the average failure probability of the left and right sides of the main section at the top, middle, and foot of the slope is 0.0820 and 0.0723, 0.0772 and 0.0492, and 0.0837 and 0.0677, respectively, indicating that the overall instability probability of the left side of the rock slope is higher than that of the right side. The rock slope with the same direction through joint is mainly affected by the joint at the toe of the slope, the rock slope with reverse through joint is mainly affected by the joint in the slope, and the sliding occurs from the middle to both ends. In addition, with the increase of the size and height of rockfall, the total energy of rock slope is also increasing, and the possibility and degree of rock slope sliding are higher. This shows that the improved particle swarm optimization algorithm can effectively analyze some factors affecting slope slip in numerical simulation of saturated rock slope slip.
Highlights
Particle swarm optimization algorithm has the advantages of simple operation and fast convergence speed, which can improve the efficiency of analysis [3, 4]. erefore, this paper proposes an improved algorithm based on particle swarm optimization algorithm and applies it to the numerical simulation of slope sliding, which provides a new idea for solving the engineering problem of rock slope stability
In this paper, based on differential evolution (DE) algorithm and simplex method, the particle swarm optimization algorithm is improved, which improves the global search ability in the initial iteration stage and the local search ability in the late iteration stage. rough comparative analysis, it is found that the algorithm in this paper has faster convergence speed and higher optimization accuracy
E traditional algorithm is always difficult to improve the analysis efficiency because of the large amount of calculation in the analysis of data of rock slope. e improved algorithm can effectively solve this problem. e stability of rock slope is analyzed by finite element method, and all simulation data are analyzed by improved particle swarm optimization (PSO) algorithm
Summary
Because of the development of traffic and economy, the construction of roads and buildings, there are a large number of rock slopes with potential safety hazards. E stability of rock slope has a direct impact on the safety of traffic and residents in nearby areas. Numerical simulation of slip of rock slope can effectively analyze the stability of rock slope, but it requires a large amount of calculation in data analysis. Particle swarm optimization algorithm has the advantages of simple operation and fast convergence speed, which can improve the efficiency of analysis [3, 4]. Erefore, this paper proposes an improved algorithm based on particle swarm optimization algorithm and applies it to the numerical simulation of slope sliding, which provides a new idea for solving the engineering problem of rock slope stability Particle swarm optimization algorithm has the advantages of simple operation and fast convergence speed, which can improve the efficiency of analysis [3, 4]. erefore, this paper proposes an improved algorithm based on particle swarm optimization algorithm and applies it to the numerical simulation of slope sliding, which provides a new idea for solving the engineering problem of rock slope stability
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