红板岩材料隐式本构模型的建立及其应用研究

ESTABILISHMENT OF IMPLICIT CONSTITUTIVE MODEL OF RED SLATE ROCK MATERIAL AND RESEARCH ON ITS APPLICATIONS

针对红板岩材料在岩土工程中所表现的大量模糊的和不确定的因素等特点 ,基于人工神经网络的学习能力 ,借助于室内岩石力学试验 ,进行了对该材料的力学本构特性进行了神经网络模拟研究 ,提出了隐式本构模型的思想和方法 ,并通过该方法对该岩石的流变试验结果进行学习 ,获得了以网络权值结构保存的力学特性知识 ,由此得到了表征红板岩应力应变本构关系的隐式本构模型。应用结果表明 ,该方法对岩土类材料本构关系的模拟研究具有很好的应用前景。

In order to understand a large amount of fuzzy and uncertain factors of red slate rock materials in geotechnical engineering, an implicit constitutive model is established on the basic of ANN(artificial neural network) method and experiment on geotechnical materials. In the paper, the ANN s learning and training are done directly on the experimental results, the knowledge of mechanical behaviors of the materials can be obtained and stored in the weight structure of a multilayer feed forward back-propagation neural network, and hence we obtain an implicit constitutive model expressing stress-strain relationships of geotechnical materials.