摘要
将人工神经网络方法应用于软土深基坑开挖施工过程中土体物性参数的识别 ,并进而通过对饱和 -非饱和土变形渗流耦合瞬态过程的有限元数值分析预测出基坑围护结构和土体的各种性状 ,从而为实现软土深基坑开挖施工过程的控制提供了依据 .工程实例分析表明 ,该方法简单实用 。
An artificial neural network method for parametric identification of deformation and seepage process in saturated unsaturated soils during braced excavation of deep foundation is proposed. Then the nonlinear mechanical behavior of unsaturated soils in deep excavation can be predicted by means of the finite element analysis. The scientific basis for construction control is provided. The numerical results provided in the engineering illustrate the good performance of the present method in computational efficiency and accuracy as it is utilized to carry out the construction control and parametric identification in deep excavation.
出处
《大连理工大学学报》
CAS
CSCD
北大核心
2001年第3期279-287,共9页
Journal of Dalian University of Technology
基金
国家基础性研究重大项目! (攀登计划 B)
关键词
深基础
参数识别
人工神经网络
有限元分析
土体
基坑开挖
deep foundation
parametric identification
artificial neural network
finite element analysis
