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Parametric Inversion Analysis Of Xiaokang Coal Mine Roadway Surrounding Rock Based On Improved Genetic Algorithm

Posted on:2012-03-07Degree:MasterType:Thesis
Country:ChinaCandidate:Q AnFull Text:PDF
GTID:2211330368984520Subject:Bridge and tunnel project
Abstract/Summary:PDF Full Text Request
A lot of sinking and driving engineering are confronted with complex rock-soil environment, so it is very difficult for us to determine rock-soil parameters mainly due to different values of elastic modulus, Poisson's ratio and ground stress in different stratums and large influence of stratum distribution. The method to determine rock mass parameters and ground stress through site test is limited, but the method of using roadway deformation to inverse and analyze rock-soil parameters and ground stress can overcome these difficulties. So, this paper adopts displacement inversion analysis method for the research.With the displacement inversion analysis of surrounding rock parameters of Xiaokang Mine roadway as target, this paper firstly analyzes and researches the principles of displacement inversion analysis for rock-soil parameters. This problem is optimization problem. Furthermore, select genetic algorithm as optimization tool to analyze the influencing factors on optimization performance of algorithm. Then, propose to combine adaptive technology with algorithm to improve its optimization ability effectively.On the basis of collecting geological and hydrologic data about Xiaokang Mine in detail, reasonably make monitoring plan to monitor roadway convergence displacement and analyze the characteristics of surrounding rock deformation to determine the stable time and deformation amount for roadway convergence. Treat the deformation amount as the necessary actually measured displacement in procedures of surrounding rock parameters inversion analysis. Apply FLAC to establish numerical model as forward procedure of roadway surrounding rock parameter inversion. Apply MATLAB software to compile the programs of genetic algorithm. Here, adaptive technology is added to genetic algorithm to realize adaptive adjustment of crossover probability and mutation probability in algorithm. Apply improved genetic algorithm to combine with FLAC to find the minimum value of inverse analysis object function to realize parameters inversion. By comparing calculation results with reference value, if precision satisfies requirements, it will provide reference for follow-up roadway design, construction and monitoring.
Keywords/Search Tags:Roadway, Parameter Inversion, meliorated Genetic Algorithm, finite element, displacement, optimization
PDF Full Text Request
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