摘要
将洞室群视为一特定系统,采用并行进化神经网络有限元(ENN-FEM)方法建立该系统与岩体力学参数之间的相对应关系。采用遗传算法分析得到对围岩稳定性最不利的参数组合,对组合中任一参数可通过参数敏感度函数分析其敏感度,并由此综合评估各软岩力学参数对洞室群稳定性的影响,确定出关键岩层以给设计和施工提供指导性建议。实例计算表明该方法是合理的,且具有智能化和综合分析的优点。
Treating the cavern group as a special system, the corresponding relationship between the system and the mechanical parameters of the rock mass is obtained by using the parallel evolutionary neural network FEM. The worst combination of parameters related to the stability of surrounding rock mass is searched out by genetic algorithms (GA). Through sensibility analysis, the synthetical evaluation of the effects of mechanical parameters of soft rock mass on the stability of cavern group is given. Moreover, the key rock mass could be determined to provide the design and construction with further instructive suggestions. The application shows that the method is reasonable and it has the advantages of intelligent and synthetical analysis.
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2004年第4期529-533,共5页
Rock and Soil Mechanics
基金
国家重点基础发展规划(No. 2002CB412708)
国家自然科学重点基金(No. 59939190)资助
关键词
并行进化神经网络有限元
力学参数
洞室群
稳定分析
Evolutionary algorithms
Finite element method
Neural networks
Rock mechanics
Stability
