A High-Precision Method for Determining Elastic Parameters in Hard Rock Using Cellular Automata and Simulated Annealing Particle Swarm Optimization

Abstract

The accurate determination of deformation characteristics in hard rock is crucial for mechanism analysis and disaster prevention. This study introduces an innovative method that integrates Cellular Automata (CA) and Simulated Annealing Particle Swarm Optimization (SA-PSO) to determine elastic properties. Unlike previous approaches, this method also combines numerical inversion with Digital Speckle Correlation Method (DSCM) to enhance accuracy. Additionally, a modified SA-PSO inversion optimization algorithm is developed to overcome the limitation of the conventional particle swarm optimization algorithm, which tends to converge to local extremum. The proposed method is validated through a comprehensive analysis of red sandstone tests featuring D-shaped holes. Results demonstrate that the proposed method achieves the global optimum in several steps, even for inversions involving multiple points for different times, thereby ensuring high accuracy. A comparison between the inversion and experimental results reveals excellent agreement in the elastic mechanical parameters. Furthermore, the influence of eccentric loading on the test results is considered, demonstrating that accounting for eccentric loading improves the consistency between the inversion and experimental results. Overall, this paper presents a high-precision method for determining elastic parameters, offering valuable guidance for indoor experiments and engineering sites that entail limited measurement points and challenging conditions.