混凝土抗压强度尺寸效应的神经网络预测模型

Neural Network Prediction Model of Concrete Compressive Strength Size Effect

为了探究各影响因素对混凝土抗压强度尺寸效应现象的作用机理,从混凝土材料层面出发,建立基于BP神经网络的混凝土抗压强度预测模型.结合大量已有试验结果,建立可考虑试件形状、截面尺寸、高宽比、养护龄期、水灰比、水泥标号和粗骨料最大粒径等7个特性影响的人工神经网络模型.根据上述输入特征,对不同截面尺寸的混凝土抗压强度进行预测分析,并研究相关因素对混凝土抗压强度尺寸效应现象的影响程度.结果表明:1)水灰比对混凝土抗压强度尺寸效应的影响较大,其值越小,抗压强度的尺寸效应越明显;2)高宽比的增大会导致尺寸效应的增强,但当高宽比大于2时,尺寸效应趋于平稳;3)粗骨料粒径的增大会导致尺寸效应现象愈加明显,但其增长速度会随着粗骨料粒径的提高而不断降低;4)试件形状对于普通混凝土的抗压强度尺寸效应现象的影响可忽略.

To explore the mechanism of the influence factors on the size effect of concrete compressive strength,a prediction model of concrete strength by BP neural network was established from the concrete material level in this study.An artificial neural network model was established by using seven input characteristics,namely,specimen shape,specimen section size,specimen height/diameter ratio,curing age,water-cement ratio,cement mark and maximum coarse aggregate particle size.According to the above input characteristics,the compressive strength of different section sizes was predicted,and the influence of various factors on concrete size effect was studied.Results show that the water-cement ratio has a great influence on the size effect of compressive strength of concrete with the decrease of its value,and the size effect becomes more obvious.The increase of the aspect ratio leads to the enhancement of size effect.When the aspect ratio is greater than 2,the size effect tends to be stable.The size effect becomes more and more obvious with the increase of the coarse aggregate size,however,the growth rate decreases with the increase of the coarse aggregate size.The influence of specimen shape on the size effect of compressive strength of ordinary concrete can be ignored.