|国家科技期刊平台
首页|期刊导航|水力发电学报|冻盐耦合作用下掺碱粉煤灰混凝土的劣化规律

冻盐耦合作用下掺碱粉煤灰混凝土的劣化规律OA北大核心CSTPCD

Deterioration of alkali-fly ash-added concrete under freezing-salt coupling effect

中文摘要英文摘要

为研究掺碱激发剂粉煤灰混凝土在硫酸盐环境下的劣化规律,分析了不同碱激发剂掺量(0%、5%、8%、10%)的粉煤灰混凝土在冻融循环和硫酸盐耦合作用下的质量损失、超声波波速损失、抗压强度损失的变化规律,同时通过电镜、EDS 能谱、XRD 衍射对变化规律进行了分析,并基于试验数据建立劣化规律人工神经网络预测模型.结果表明,加入碱激发剂后,补尝了由于粉煤灰水化消耗的水泥水化产生氢氧化钙,有利于维持混凝土碱平衡;有效提高了粉煤灰混凝土的耐久性,碱激发剂掺量 8%时为最佳.试件的劣化程度与冻融次数表现为线性正相关;在质量损失方面,不同掺量的试件呈现出平稳下降和加速下降两个阶段,其中未掺碱激发剂的试件加速下降阶段出现较早;在超声波波速损失、抗压强度损失方面,掺了碱激发剂的试件只出现了平稳下降的阶段;通过微观分析可知,造成掺碱激发剂粉煤灰混凝土劣化过程加剧的主要原因是石膏和钙钒石的逐渐生成;建立的人工神经网络预测模型具有较高的精度.

To study the deterioration of alkali-excited fly ash concrete under sulfate environment,this paper studies the variations in mass loss,ultrasonic wave velocity loss,and compressive strength loss of fly ash concrete,by examining the specimens of different alkali admixtures(0%,5%,8%,and 10%)under the coupling of freeze-thaw cycling and different sulfate contents.We determine deterioration patterns through experimental tests using electron microscopy,EDS energy spectroscopy,and XRD diffraction,and develop an artificial neural network prediction model of deterioration patterns based on the test data.The results show adding alkaline exciters improves the durability of fly ash concrete significantly at the optimal alkali admixture of 8%.The deterioration of the specimens shows a linear positive correlation with the number of freeze-thaw cycles.In terms of mass loss,the specimens with different dosages show two stages,smooth declining and accelerated declining;the latter stage appears earlier for the specimens without the alkali exciter.In terms of the loss of ultrasonic wave velocity and the loss of compressive strength,the specimens doped with alkali exciters show only a steady declining stage.Microscopic analysis reveals that the intensified deterioration of alkali-excited fly ash concrete is caused by gradual generation of gypsum and calcovanadate,and our artificial neural network prediction model has high accuracy.

邵善庆;龚爱民;屈宝莉;王福来;罗加辉;雍康;金镯

云南农业大学 水利学院,昆明 650201天启工程咨询有限公司,昆明 650201

土木建筑

劣化碱激发剂冻融硫酸盐微观人工神经网络

deteriorationalkali-excitedfreeze and thawsulfatemicroscopicartificial neural network

《水力发电学报》 2024 (005)

115-122 / 8

云南省教育厅科学研究基金项目(2022Y286)

10.11660/slfdxb.20240511

评论