应力状态下混凝土受硫酸盐侵蚀深度的神经网络预测分析

Neural Network Prediction of Sulfate Attack Depth of Concrete under Stress States

基于BP神经网络算法,以硫酸盐侵蚀混凝土试验数据为训练样本,建立了考虑硫酸盐侵蚀溶液浓度、混凝土拉压应力水平和侵蚀时间等影响因素的硫酸盐侵蚀混凝土深度的内推与外推预测模型.经验证,该模型具有良好的预测效果,为混凝土受硫酸盐侵蚀的耐久性研究提供了一种有效方法.

Based on BP neural network algorithm,utilizing the experimental data of concrete under sulfate corrosion as the training samples,the models are proposed for inside and outside predicting the corrosion depth of concrete,which consider the influence factors of the concentration of sulfate radical in solution,the tensile and compressive stress levels of concrete and the corrosion time.It is verified that the proposed model is of well forecasting ability,and is a new method for durability study of concrete unde...