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个人信息Personal Information
教授
硕士生导师
性别:女
毕业院校:沈阳工业大学
学位:硕士
所在单位:土木工程系
学科:结构工程. 工程力学
办公地点:土木工程学院(综合实验三号楼)525
电子邮箱:lhhang@dlut.edu.cn
基于BP神经网络的FRP筋与混凝土界面黏结强度预测
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发表时间:2021-01-01
发表刊物:Journal of Dalian University of Technology
卷号:61
期号:3
页面范围:272-279
ISSN号:1000-8608
关键字:"ANN; ANN; BP neural network model; FRP reinforced concrete; bond strength; prediction"
CN号:21-1117/N
摘要:The interface bond strength of FRP(fiber reinforced polymer)reinforced concrete is one of the important indicators to evaluate its mechanical properties.Based on the experimental data available in the literature,a database including 292 groups of pull-out test results of FRP reinforced concrete is established,and thus the bond strength between FRP bars and concrete is predicted by using artificial neural network.The database is randomly divided into two data sets,of which 242 groups of data are used for training and 50 groups of data are used for simulation prediction.A threelayer artificial neural network model is trained by using the back propagation algorithm,where seven parameters are considered in the input layer,namely FRP type,surface form,FRP rebar diameter, anchorage length,failure mode,concrete compressive strength and normalized concrete cover thickness.The output layer is specified as the interface bond strength between FRP bars and concrete.The results indicate that the BP neural network model has strong capability of prediction and generalization,and the predicting error is minor.This method can integrate many considerations those influence the interface bond strength between FRP bars and concrete,and give out accurate predicting results.
备注:新增回溯数据