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Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors

XU Bo WU Zhi-min SONG Zhi-fei

西南交通大学学报（英文版）2007，Vol.15Issue(3)：218-222,5.

Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors

XU Bo ¹WU Zhi-min ²SONG Zhi-fei¹

作者信息

1. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China
2. Dalian Civil Engineering Quality Supervision Office, Dalian 116012, China
折叠

摘要

Abstract

To predict the tensile capacity of adhesive anchors, a multilayered feed-forward neural network trained with the backpropagation algorithm is constructed. The ANN model have 5 inputs, including the compressive strength of concrete, tensile strength of concrete, anchor diameter, hole diameter, embedment of anchors, and ultimate load. The predictions obtained from the trained ANN show a good agreement with the experiments. Meanwhile, the predicted ultinate tensile capacity of anchors is close to the one calculated from the strength formula of the combined cone-bond failure model.

关键词

Artificial neural network/Concrete/Adhesive anchors/Ultimate tensile capacity/Model

Key words

Artificial neural network/Concrete/Adhesive anchors/Ultimate tensile capacity/Model

分类

计算机与自动化

引用本文复制引用

XU Bo,WU Zhi-min,SONG Zhi-fei..Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors[J].西南交通大学学报（英文版）,2007,15(3):218-222,5.

基金项目

The National Natural Science Foundation of China ( No. 50578025) （ No. 50578025）

西南交通大学学报（英文版）

ISSN：2662-4745

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