【摘要】 岩体力学参数对地下洞室的施工和设计是极其重要的,通过位移反分析确定岩体参数的应用研究很多。为了提高参数反演的效率,采用均匀设计理论设计不同的反演参数组合,用有限元计算组建的样本集训练神经网络,根据洞室开挖过程中实测位移反演地下洞室岩体力学参数。基于面向对象、自适应、可视化三大关键技术,开发了地下洞室岩体力学参数反演有限元软件系统BAFES。该软件可实现地下洞室力学参数反演分析、开挖预报过程的可视化,将地下洞室岩体力学参数反演模式由“数据-有限元分析-数据”转变为“图形-有限元分析-图形”,结合现场监控技术和工程稳定分析,能及时地指导工程设计和施工。以某水电站地下厂房洞室群岩体力学参数反演为例,说明了该软件的实用性。更多还原

【Abstract】 Rock-mass parameters are very important to underground cavern design and construction;many application studies about calculating rock-mass parameters have been implemented by back analysis of displacements.In order to improve parameters back analysis,the uniformity design theory is introduced to design training swatch for neural networks,rock-mass mechanical parameters of underground cavern are obtained from measured displacement messages.The back analysis finite element software is implemented based on three key techniques: object-oriented,adaptability and visualization,which can be used as visualized back analysis and forecast tool.Rock-mass parameters back analysis is implemented by mean of “graph-finite element analysis-graph” instead of “data-finite element analysis-data”,it can instruct design and construction in time with monitoring technique and stabilization analysis.It is illustrated that this software is very useful by the example of the underground cavern of a hydropower project.更多还原