人工冻结黏土广义开尔文蠕变本构模型模糊随机优化

冻土的蠕变本构模型是冻结法建井的重要参考资料。在-5℃、-10℃、-15℃和-20℃下，针对人工冻结黏土进行不同应力等级的单轴蠕变试验，获得不同温度、不同应力等级条件下蠕变曲线的变化规律。通过模糊随机迭代搜索改进传统的Guess-Newton算法，得到模糊随机Guess-Newton算法步骤，利用改进的算法优化广义开尔文本构模型参数，获得各温度和应力下的优化蠕变模型。工程试验表明:模糊随机Guess-Newton算法能有效地优化广义开尔文本构模型参数，使模型更好地拟合冻土各阶段的蠕变值，准确地表征了冻土的蠕变特性，同时改进后的算法较传统的算法效率更高，收敛更快。 

Fuzzy random optimization of generalized Kelvin constitutive model for creep of artificial freezing clay

The constitutive model of freezing creep is one of the important reference data for shaft building using freezing method. Uniaxial creep tests under different stress levels were conducted for the artificial freezing clay at -5℃, -10℃, -15℃ and -20℃. So the changing rules of creep curves were obtained under the condition of different temperatures and different stress levels. On this basis, traditional Guess-Newton algorithm has been improved by fuzzy random iterative search and the of the fuzzy random Guess-Newton algorithm steps were obtained, then we use the improved algorithm to optimize the parameters of the generalized Kelvin constructive model, obtained the optimized creep model under various temperature and stress. Engineering experiments show that fuzzy random Guess-Newton algorithm can effectively optimize generalized Kelvin constitutive model parameters, thus making the model better fit to creep values of freezing clay at each stage and accurately representing of the creep characteristics of freezing clay. At the same time, the improved algorithm is more efficient and faster convergent than the traditional algorithm.