人工神经网络
弯曲
结构工程
均方误差
有限元法
一般化
近似误差
强度因子
计算机科学
材料科学
数学
工程类
算法
数学分析
人工智能
统计
作者
Xiaohong Li,Xianghui Li,Bin Chen
摘要
Using ANSYS software to establish the finite element model of crack bending tube, the SIF at the tip of the crack is calculated for the difference in the diameter of the pipe, the outer diameter of the elbow, and the bending angle of the bend pipe, and it is used as a neural network to calculate the sample. By using three layers of BP network to establish the prediction model of the SIF of cracked pipe, the simulation of 39 sets of samples proves that the relative error of the BP network model is 0.19% and the mean square error of the network output is 0.0102. The prediction model has high prediction precision and generalization ability and can be used in engineering design and calculation.
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