Optimization Design And Application Of Rock-like Material Ratio Based On Genetic Algorithm Inversion And Forward Modeling

In order to ensure the smooth construction of the project and the safety and stability of the later stage,it is extremely important to study the rock mechanics properties of the rock mass.Based on this problem,this thesis adopts the method of determining the target rock and preparing rock-like materials,which can effectively restore the macroscopic mechanical properties and failure characteristics of the target rock under loading conditions.However,it is always a difficult task to characterize the mechanical properties of the prepared rock-like materials to the maximum extent similar to the target rock.Therefore,by means of experimental design,statistical test and the establishment of proportion-optimization model,this thesis will study the optimization problem of rock-like materials proportion-optimization.The main research work and conclusions of this thesis include the following aspects:(1)Rock-like materials were prepared based on 1/15 tension-compression ratio of target rock as the main reference index and 7 macro mechanical parameters as similarity standards.The ratio of water and paste,iron powder content and coarse sand content were selected as the ratio factors for the orthogonal test design to obtain 25 groups of ratio combinations.(2)Uniaxial compression,Brazilian splitting,direct shear and triaxial compression were carried out in 25 experimental groups respectively,and 7 macromechanical parameters corresponding to each ratio combination were obtained.The failure characteristics of rock-like material and target rock under the same loading conditions are basically the same,that is,the highly brittle tensile failure.(3)Based on the sensitivity analysis of orthogonal experimental design,the quantitative relationship between the ratio factors of rock-like materials and macroscopic mechanical parameters was studied,and the influence law and the influence degree of various ratio factors on various macroscopic parameters were obtained.The quantitative relationship between the ratio factors and macro parameters was fitted out,which laid a foundation for the subsequent programming of inverse ratio optimization based on genetic algorithm.The reliability of 25 groups of experimental results was verified by multiple linear regression method.(4)Based on the above quantitative relationship,a genetic algorithm-based inverse proportioning optimization program is constructed in the MATLAB environment,and the output results are tested.The results show that the method can achieve better optimization effect;In addition,the forward ratio optimization program based on genetic algorithm is constructed and the optimal ratio is obtained in the fifth generation cycle.Finally,the two kinds of ratio optimization programs are compared to analyze their advantages and disadvantages.(5)The optimal ratio of the output results of the above two programs is selected to conduct the academic application research of the surrounding rock model of the simulated 1/15 tension-compression ratio under uniaxial loading condition,and verify the optimization results mentioned above.During the loading process,acoustic emission monitoring equipment and VIC non-contact full-field strain measurement system were used to observe simultaneously to analyze the crack propagation mechanism and final failure mode of the surrounding rock models with two shapes.