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冻盐耦合作用下掺碱粉煤灰混凝土的劣化规律

邵善庆 龚爱民 屈宝莉 王福来 罗加辉 雍康 金镯

水力发电学报2024,Vol.43Issue(5):115-122,8.
水力发电学报2024,Vol.43Issue(5):115-122,8.DOI:10.11660/slfdxb.20240511

冻盐耦合作用下掺碱粉煤灰混凝土的劣化规律

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

邵善庆 1龚爱民 1屈宝莉 2王福来 1罗加辉 1雍康 1金镯1

作者信息

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

摘要

Abstract

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.

关键词

劣化/碱激发剂/冻融/硫酸盐/微观/人工神经网络

Key words

deterioration/alkali-excited/freeze and thaw/sulfate/microscopic/artificial neural network

分类

土木建筑

引用本文复制引用

邵善庆,龚爱民,屈宝莉,王福来,罗加辉,雍康,金镯..冻盐耦合作用下掺碱粉煤灰混凝土的劣化规律[J].水力发电学报,2024,43(5):115-122,8.

基金项目

云南省教育厅科学研究基金项目(2022Y286) (2022Y286)

水力发电学报

OA北大核心CSTPCD

1003-1243

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