摘要
宾汉极限切应力是描述非牛顿体流变特性的一个重要参数,由于流体中泥沙颗粒之间作用的复杂性,使得宾汉极限切应力的理论分析还不完善,其解析计算也较繁琐.基于BP神经网络的宾汉极限切应力的计算和预测,避开不完善的理论分析,把已知的影响因子提供给网络,网络给出宾汉极限切应力的预测值.仿真结果表明,神经网络训练的结果与实测值吻合,显示了神经网络在宾汉极限切应力的计算和预测中优势.
The Bingham yield stress is an important parameter to descript the characteristics of hyperconcentration fluid.As the role between the sands is so complex,the theoretical analysis of the Bingham yield stress has not been so perfect,and the analyzed calculation was much multitudinous.The calculation and prediction of the Bingham yield stress using BP neural network avoid the imperfect theoretical analysis,and with this method while the known impact-factors were provided,the neural network outputs the prediction.The simulation results show that the prediction are approaching to the measured,which showed the superiority of the neural network to calculat and predict the Bingham yield stress of hyperconcentration fluid.
出处
《河南科学》
2009年第4期437-440,共4页
Henan Science
基金
国家自然科学基金资助(50339050)
