欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
单位时间内通过混凝土结构的总电荷量是反映混凝土结构氯离子渗透能力的一个重要指标。针对传统经验公式法预测了氯离子总电荷量的不足，建立了一个模糊神经网络模型以预测氯离子总电荷量。此模型能同时考虑多种因素及其非线性耦合作用，方便易行、通用性好，较之其它神经网络具有运算速度快、不容易陷入局部最优、训练效果好的特点。训练样本训练后的结果表明，该模型具有较高的准确度，能可靠预测氯离子总电荷量，准确评价混凝土结构的抗氯盐侵蚀能力，为实际工程的耐久性设计和评价提供依据。
英文摘要：
Chloride permeability of concretes, which is determined through rapid chloride permeability test （RCPT） ,is an important indicator of the ability of chloride ion penetration in concrete. Because it is inaccurate to be predicated by the traditional empirical formula, a new model, based on neural network and fuzzy theory, has been proposed to estimate chloride permeability of concrete. Many related factors and the non-linear coupling effects of them have been taken into account. This model is simple for use and can be effective on many occasions. Compared with other neural networks, the method is better not only because of its high-speed in calculation but also its refusal of local optimum. After training, the testing results show that it has high accuracy. In short, the model is able to predict chloride permeability of concrete reliably and provide assistance for the estimation of durability in practical project designs.
同期刊论文项目
同项目期刊论文
Field inspection on chloride ion-intrusion effect of seawater in dry-wet cycling zone of concrete st
Determination and application of the sharp degradation point of concrete under environmental actions
Spatial variability-based corrosion risk assessment and strategy of repair and maintenance for RC st
期刊信息
位置：