混凝土拌和物坍落度预测方法的研究  

Study on Prediction Method of Fresh Concrete Slump

作　　者：季韬[1] 林挺伟[1] 郑忠双[2] 林旭健[1] 

机构地区：[1]福州大学土木建筑工程学院,福建福州350002 [2]福建省抗震防灾技术中心,福建福州350001

出　　处：《建筑材料学报》2005年第2期159-163,共5页Journal of Building Materials

基　　金：福建建工青年基金资助项目

摘　　要：在给出混凝土名义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,建立了混凝土拌和物坍落度与混凝土名义水灰比、骨料平均浆体厚度、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,并为高体积稳定性混凝土配合比设计方法的进一步探讨奠定基础.The slump of fresh concrete depends on three parameters-nominal water-cement ratio of concrete, average paste thickness of aggregates and fly ash-binder ratio. Applying two concepts of characteristic diameter and eigenpacking degree, the differences between theoretical model and actuality of fine and coarse aggregates can be eliminated. Based on the calculation methods of nominal water-cement ratio of concrete and average paste thickness of aggregates provided by authors, the nonlinear relation ship between slump of fresh concrete and nominal water-cement ratio of concrete, average paste thickness of aggregates, fly ash-binder ratio is established by applying artificial neural network. The outcome of the study can be used to reduce the number of trial and error in concrete mix proportion design, save cost and labor, and can lay the foundation of mix proportion design of higher volume-stability concrete.

关 键 词：混凝土拌和物 坍落度 预测方法 人工神经网络方法 非线性映射关系 混凝土配合比 体积稳定性 计算方法 研究成果 胶凝材料 设计方法 水灰比 粉煤灰 基础 厚度 浆体 平均 骨料 试配 

分 类 号：TU528.042[建筑科学—建筑技术科学] TV431[水利工程—水工结构工程]