基于人工神经网络的混凝土抗压强度预测方法

Prediction Method of Concrete Compressive Strength Based on Artificial Neural Network

在给出混凝土等效水灰比和骨料平均浆体厚度计算方法的基础上,采用人工神经网络方法,建立了混凝土28 d抗压强度与混凝土等效水灰比、骨料平均浆体厚度和粉煤灰与胶凝材料用量比之间的非线性映射关系.该研究成果可减少混凝土试配次数,节约大量人力、物力和时间,并为高体积稳定性混凝土配合比设计方法的研究进一步奠定了基础.

Based on the calculation methods of equivalent water-cement ratio of concrete and average paste thickness of aggregates provided by authors, the nonlinear relation between 28 d concrete compressive strength and equivalent water-cement ratio of concrete, average paste thickness of aggregates, fly ash-binder ratio is established by using artificial neural network. The outcome can be used to reduce the number of trial and error, save cost, labor and time in concrete mix proportion design, and can further lay the foundation for the mix proportion design of high volumestability concrete.