Chloride ingress analysis on alkali-activated slag concrete: A validated modelling framework for long-term assessment

被引:2
作者
Dong, Bin [1 ]
Yu, Yuguo [2 ]
Feng, Yuan [1 ]
Yang, Jie [3 ]
Zhao, Gaofeng [4 ]
Gao, Wei [1 ]
机构
[1] Univ New South Wales, Ctr Infrastruct Engn & Safety, Sch Civil & Environm Engn, Sydney, NSW 2052, Australia
[2] RMIT Univ, Sch Engn, Civil & Infrastruct Engn, Melbourne, Vic 3000, Australia
[3] RMIT Univ, Sch Engn, POB 71, Bundoora, Vic 3083, Australia
[4] Tianjin Univ, Sch Civil Engn, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300354, Peoples R China
来源
JOURNAL OF BUILDING ENGINEERING | 2024年 / 93卷
基金
澳大利亚研究理事会;
关键词
Alkali-activated slag concrete; Finite element analysis; Gibbs energy minimisation; Hybrid chloride binding modelling; Long -term chloride ingress; FLY-ASH; TRANSPORT; EVOLUTION; MORTARS; CEMENTS;
D O I
10.1016/j.jobe.2024.109867
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Amidst global commitment to reduce CO2 emissions, the forthcoming decades expect to witness the prevalence of alkali-activated materials. As a predominant trigger for reinforcement corrosion, the accurate prediction of chloride ingress is paramount for the widespread application of the emerging building material. In this regard, this paper presents a novel framework tailored for analysing long-term chloride penetration into alkali-activated slag (AAS) concrete. An innovative technique for modelling chloride binding is developed and integrated into the framework. The technique can spontaneously assess time-dependent chloride binding based on the detailed phase assemblage, thereby rendering the framework applicability for the long-term analysis. The effectiveness of this model is rigorously validated against experiments. Furthermore, a series of virtual experiments are conducted by using the verified model to investigate the impact of different activators, where the distinction of resulting AAS concretes in resisting chloride ingress is elucidated. Overall, the present model is promising in delivering comprehensive understanding and robust prediction concerning long-term behaviours of next-generation AAS concrete buildings.
引用
收藏
页数:17
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