拉剪组合状态下的锚杆极限承载力分析——基于BP神经网络

Estimation of Bearing Capacity of Anchors under Combined Tension and Shear Based on BP Neural Network

锚杆在拉剪组合状态下的极限承载力受锚杆及混凝土的力学特性、锚固及加载方式、锚杆的直径及植入深度等诸多因素的影响.基于BP神经网络,提出了拉剪组合状态下锚杆极限承载力预测模型;考虑影响锚杆极限承载力的主要因素,用实测试验数据建立模型.通过模型验证及参数分析表明,BP神经网络模型对锚杆在拉剪组合状态下的极限承载力预测的效果良好,在实际工程应用中有一定参考价值.

Bearing capacity of self-locked anchor under combined tension and shear can be influenced by many factors, such as the mechanical characters of bolts and concrete, the means of anchoring and loading, and the diameter and anchorage length of the bolts and so on. Based on BP neural network, a forecast model about bearing capacity of self-locked anchor under combined tension and shear is presented. The model is established in considering the main impact factor grounded on experimental data. The results indicate that this method is proven and effective in estimation of bearing capacity of bolts un- der combined tension and shear, and it can be used to solve similar problems in practical engineering.