中文摘要：

海相沉积软土具有很强的蠕变特性,传统分级构建蠕变本构模型方法不实用,且很难真正反映岩土流变的非线性特性。为此,本文引入具有超强非线性映射和容错能力的BP神经网络模型,通过改进BP算法,根据江门软土的室内直剪蠕变试验结果,建立了海相沉积软土BP神经网络蠕变本构模型,避免了传统方法为满足试验曲线变化规律和蠕变特性而需要建立复杂的本构数学表达式。最后,利用上海地区软土蠕变实验结果对本文提出的方法进行了验证,并对BP神经网络蠕变模型在描述软土流变方面的特点进行了讨论。结果表明,本文建模方法简单,并能很好地描述软土的非线性蠕变问题。

英文摘要：

Marine sediment clay has higher creep characteristic. Traditional rheological constitutive models built under each level loading are impractical and hard to describe the nonlinear properties of rheology of rock and soil really. So, the BP neural network is introduced in the text. It has strong nonlinear mapping ability and fault - tolerance ability. Through improving the algorithm of BP, the BP constitutive model is built directly. The model is based on the creep data of laboratory direct shear experiment. It could avoid building a necessary complex constitu- tive equation in order to meeting the variable law of trial curve and creep character. At the end, the modeling method is tested by the creep experimental data of soft clay of Shanghai and the features of BP neural network rheological model on describing creep curves of soft clay are discussed. It is shown that the rheological model is simple and can effectively describe nonlinear creep of soil clay with better prediction.