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实时准确地获得地下洞室岩体的力学参数对地下工程的设计和施工具有重要影响。以某软岩区的水电站引水隧洞为例,基于卸荷岩体力学理论,以大型有限差分程序FLAC3D为计算软件,建立BP神经网络模型对开挖后围岩的力学参数进行反分析,并根据现场实测位移资料对反演所得参数进行工程校核,以保证参数取值的准确性。结果表明,该反演方法合理、有效;得到的参数能满足工程要求,可为隧洞围岩的长期稳定和位移变化预测提供理论依据。
Real-time and accurate access to the mechanical parameters of underground cavern rock mass has an important influence on the design and construction of underground engineering. Taking the diversion tunnel of a hydropower station in a soft rock area as an example, based on the mechanical theory of unloading rock mass, a large-scale finite-difference program FLAC3D is used as a calculation software to establish a BP neural network model to inverse analyze the mechanical parameters of the surrounding rock after excavation. Field measured displacement data of the parameters of the inversion of engineering verification, in order to ensure the accuracy of parameter values. The results show that the inversion method is reasonable and effective. The obtained parameters can meet the engineering requirements and provide a theoretical basis for long-term stability and displacement prediction of tunnel surrounding rock.