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| Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors | |
| 作者姓名： | 徐波 吴智敏 宋志飞 |
| 作者单位： | State Key Laboratory of Coastal and Offshore Engineering Dalian University of Technology，State Key Laboratory of Coastal and Offshore Engineering，Dalian University of Technology，Institute of Civil Engineering，Liaoning Technical University，Dalian 116024 China，Dalian Civil Engineering Quality Supervision Office，Dalian 116012 China，Dalian 116024，Fuxin 123000 China |
| 基金项目： | Foundation item The National Natural Science Foundation of China （ No. 50578025 ） |
| 摘 要： | To predict the tensile capacity of adhesive anchors, a multilayered feed-forward neural network trained with the back-propagation 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 ultimate tensile capacity of anchors is close to the one calculated from the strength formula of the combined cone-bond failure model. |
| 关 键 词： | 人工神经网络 混凝土 粘合剂 可变容量 |
| 文章编号： | 1005-2429（2007）03-0218-05 |
| 修稿时间： | 2006-06-29 |
Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors |
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| XU Bo,WU Zhi-min,SONG Zhi-fei.Artificial Neural Network Model for Predicting Ultimate Tensile Capacity of Adhesive Anchors[J].Journal of Southwest Jiaotong University,2007,15(3):218-222. | |
| Authors: | XU Bo WU Zhi-min SONG Zhi-fei |
| Institution: | 1. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China;Dalian Civil Engineering Quality Supervision Office, Dalian 116012, China 2. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China 3. Institute of Civil Engineering, Liaoning Technical University, Fuxin 123000, China |
| Abstract: | To predict the tensile capacity of adhesive anchors, a multilayered feed-forward neural network trained with the back-propagation 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 ultimate tensile capacity of anchors is close to the one calculated from the strength formula of the combined cone-bond failure model. |
| Keywords: | Artificial neural network Concrete Adhesive anchors Ultimate tensile capacity Model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |