Study on the deterioration of concrete performance in saline soil area under the combined effect of high low temperatures, chloride and sulfate salts

硫酸盐 材料科学 氯化物 水泥 腐蚀 粉煤灰 土壤盐分 腐蚀 多孔性 含水量 玄武岩纤维 复合材料 岩土工程 纤维 冶金 土壤科学 土壤水分 环境科学 地质学 古生物学
作者
Daming Luo,Fan Li,Ditao Niu
出处
期刊:Cement & Concrete Composites [Elsevier BV]
卷期号:150: 105531-105531 被引量:95
标识
DOI:10.1016/j.cemconcomp.2024.105531
摘要

Concrete structures in saline soil regions are prone to degradation due to chloride and sulfate erosion, compounded by the concurrent influences of drying, high and low temperatures, and freeze-thaw cycles. This study establishes a simulation test system for complex saline soil environments, integrating findings from real-world environmental investigations. The investigation focused on the degradation mechanism of concrete under the combined impacts of dry-wet and high-low temperature cycles, coupled with composite salt erosion. Additionally, the impacts of water-cement ratio, fly ash content, and basalt fiber content on concrete's mechanical properties and ion erosion resistance were analyzed. The alterations in the internal pore structure of corroded concrete were examined through nuclear magnetic resonance (NMR) technology. Utilizing the XGBoost algorithm, a predictive model for chloride and sulfate ion concentrations in concrete, under the combined influence of dry-wet and high-low temperature cycles, coupled with composite salt erosion, was developed. The findings reveal that the rate of concrete deterioration is gradually accelerating under the combined erosion to dry-wet cycles, high-low temperature cycles, and composite salt. Optimal fly ash and basalt fiber dosages for corrosion resistance are determined to be 10% and 0.10%, respectively. During advanced erosion stages, concrete porosity, capillary and macropore volume fractions increase, while gel pore volume fraction declines significantly. The XGBoost-based chloride and sulfate concentration prediction model demonstrates strong agreement with experimental measurements, yielding correlation indices of R2 = 0.98 and 0.97, respectively. Interpretation results obtained using SHAP from the machine learning model align with experimental outcomes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
杨瑞鹏发布了新的文献求助10
刚刚
搞怪人雄发布了新的文献求助10
1秒前
FashionBoy应助Teen采纳,获得10
1秒前
wonderingria发布了新的文献求助10
2秒前
2秒前
2361WE完成签到,获得积分20
3秒前
杨朝进发布了新的文献求助10
3秒前
3秒前
丘比特应助tomqas采纳,获得10
5秒前
5秒前
李李发布了新的文献求助10
5秒前
dax大雄完成签到 ,获得积分10
6秒前
8秒前
Laolin完成签到 ,获得积分10
9秒前
柒鹿发布了新的文献求助10
9秒前
cdercder应助杨朝进采纳,获得10
9秒前
ccw发布了新的文献求助10
9秒前
mojomars发布了新的文献求助10
10秒前
杨晓白完成签到,获得积分10
10秒前
zaza完成签到,获得积分10
11秒前
12秒前
13秒前
13秒前
科研通AI6.2应助ahui采纳,获得10
15秒前
guan发布了新的文献求助10
15秒前
15秒前
asplD完成签到,获得积分10
16秒前
16秒前
赘婿应助王晨旭采纳,获得10
17秒前
Joy发布了新的文献求助10
18秒前
tomqas发布了新的文献求助10
18秒前
ccw完成签到,获得积分20
18秒前
温柔的曼梅完成签到 ,获得积分10
18秒前
shufessm完成签到,获得积分10
19秒前
科研顺利发布了新的文献求助10
19秒前
20秒前
20秒前
20秒前
YQT完成签到,获得积分10
21秒前
英勇的飞凤完成签到,获得积分10
21秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Bend stiffness of submarine cables – an experimental and numerical investigation 5000
Advanced Weaponeering Fourth Edition, Volume 2 1000
Weaponeering: An Introduction Fourth Edition, Volume 1 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7541757
求助须知:如何正确求助?哪些是违规求助? 9125905
关于积分的说明 19497327
捐赠科研通 7138006
什么是DOI,文献DOI怎么找? 3258351
关于科研通互助平台的介绍 2425643
邀请新用户注册赠送积分活动 2246454