PREDICTION OF LONG-TERM STRENGTH OF CONCRETE BASED ON ARTIFICIAL NEURAL NETWORK

摘要：

　　Recently,the safety of existing civil engineering structures attracts more and more attention.The long-term strength of concrete plays a key role during the assessment of safety and durability for civil engineering structures.The strength of concrete will gradually decrease during the service of civil engineering structures.It is significant to accurately predict the strength deterioration of concrete for correctly evaluating the safety of structures.The factors affecting the long-term strength of concrete inctude environment type,age,climate,water cement ratio,amount of cementing material and so on.In this paper,artificial neural network with powerful mapping ability has been selected to predict the long-term strength of concrete.First,there-layer BP neural network with age,water cement ratio,amount of cementing material as input and long-term strength as output was built.Then,the neural network was trained by the samples measured in real structures and the well-trained neural network was test.From the test results,the trained neural network can accurately predict the lone-term strength of concrete with the error less then 9%.

关键词： Concrete long-term strength artificial neural network prediction

作者: Xiaoming Yang Dan Shi

作者单位: College of Civil Engineering and Architecture, Liaoning Technical University, Fuxin 123000, P.R.China

会议类型: 国际会议

会议名称: The Twelfth International Symposium on Structural Engineering (第十二届结构工程国际研讨会)

会议地点: 武汉

会议语种:英文

页码: 211-215

在线出版日期: 2012-11-17（万方平台首次上网日期，不代表论文的发表时间）