人工神经网络在受腐蚀钢筋混凝土结构工程中的应用

State-of-the-art on application of artificial neural networks in corroded reinforced concrete structural engineering

介绍了人工神经网络在土木工程中的应用现状,阐述了人工神经网络在受腐蚀钢筋混凝土结构工程中的应用,介绍了神经网络方法在锈蚀钢筋与混凝土之间粘结特性及受腐蚀钢筋混凝土构件受力性能研究中新近取得的研究成果。研究表明,与传统的回归方法相比,神经网络方法在解决多影响因子复杂非线性问题方面具有显著的优势,在受腐蚀钢筋混凝土结构工程中具有广阔的应用前景。

Application of Artificial Neural Networks(ANNs)in civil engineering was introduced in this paper.The approach about using artificial neural networks in corroded R.C.structural engineering was discussed.Then,recent research results,which focus on the application of ANNs in the study of bond strength between rusty rebar and concrete and the ultimate strength of corroded R.C.beams,were reported.It is shown that ANNs has remarkable advantages than the conventional regression method in the field of solving the complex multi-factor nonlinear problems.With the development of this technology,ANNs is promising in the research on corroded R.C.structural engineering.