化学腐蚀下岩石应力应变进化神经网络本构模型

提出一种反映化学腐蚀下岩石全应力 应变特征的进化神经网络本构模型·该模型不同于常规的本构模型,化学腐蚀影响下全应力 应变特征反映在其网络结构和网络权值上;该模型结构是由遗传算法搜索得到的,具有很好的预测功能;模型经过训练较好地反映同种矿物质在不同化学溶液的腐蚀下全应力 应变普遍特征·实例表明该模型描述了化学溶液的腐蚀下岩石全应力 应变普遍特征且有较好的推广预测功能·

Evolutionary Neural Network Constitutive Model for Complete Stress-Strain Relationship of Rock Under Chemical Corrosion

An evolutionary neural network constitutive model is proposed to describe the whole stress-strain process of rock under chemical corrosion. Differing from other conventional models, the model reflects the whole stress-strain process of rock under chemical corrosion in terms of its network topology and weights and it is constituted by genetic algorithm with favorable prediction function provided. After training with samples in which sufficient stress-strain information are involved, the model will indicate the complete stress-strain relationship of a mineral that is the same to the sample which has been corroded by different chemical solutions. This has been proved by a practical example. The model is thus recommended to apply to predicting the whole stress-strain process of a rock that didn't participate in the training by evolutionary neural network.