摘要
To determine structure and parameters of a rheological constitutive model for rocks,a new method based on differential evolution(DE) algorithm combined with FLAC3D(a numerical code for geotechnical engineering) was proposed for identification of the global optimum coupled of model structure and its parameters.At first,stochastic coupled mode was initialized,the difference in displacement between the numerical value and in-situ measurements was regarded as fitness value to evaluate quality of the coupled mode.Then the coupled-mode was updated continually using DE rule until the optimal parameters were found.Thus,coupled-mode was identified adaptively during back analysis process.The results of applications to Jinping tunnels in China show that the method is feasible and efficient for identifying the coupled-mode of constitutive structure and its parameters.The method overcomes the limitation of the traditional method and improves significantly precision and speed of displacement back analysis process.
To determine structure and parameters of a rheological constitutive model for rocks, a new method based on differential evolution (DE) algorithm combined with FLAC3D (a numerical code for geotechnical engineering) was proposed for identification of the global optimum coupled of model structure and its parameters. At first, stochastic coupled mode was initialized, the difference in displacement between the numerical value and in-situ measurements was regarded as fitness value to evaluate quality of the coupled mode. Then the coupled-mode was updated continually using DE rule until the optimal parameters were found. Thus, coupled-mode was identified adaptively during back analysis process. The results of applications to Jinping tunnels in China show that the method is feasible and efficient for identifying the coupled-mode of constitutive structure and its parameters. The method overcomes the limitation of the traditional method and improves significantly precision and speed of displacement back analysis process.
基金
Project (50809017) supported by the National Natural Science Foundation of China