Study and Neural Network Analysis on Durability of Basalt Fibre Concrete

被引:5
|
作者
Shao, Shanqing [1 ]
Wang, Ran [1 ]
Gong, Aimin [1 ]
Li, Ruijun [2 ]
Xu, Jing [3 ]
Wang, Fulai [1 ]
Liu, Feipeng [3 ,4 ]
机构
[1] Yunnan Agr Univ, Coll Water Conservancy, Kunming 650201, Peoples R China
[2] Hubei Acad Water Resources & Hydropower Sci, 286 Luoshi South Rd, Wuhan 430070, Peoples R China
[3] Yunnan Univ, Inst Int Rivers & Ecosecur, Kunming 650500, Peoples R China
[4] Natl Forestry & Grassland Adm, Southwest Survey & Planning Inst, Kunming 650031, Peoples R China
关键词
basalt fibres; durability; artificial neural networks; grey cluster analysis; ALKALI-ACTIVATED METAKAOLIN; COMPRESSIVE STRENGTH; PREDICTION; BEHAVIOR;
D O I
10.3390/w15061016
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In order to investigate the law of basalt fibre to enhance the durability of concrete, this paper selects basalt fibre length as the main factor, supplemented by novel research methods such as neural networks, to study the rule of concrete resistance to multiple types of salt erosion. Tests have shown that large doses of mineral admixtures and basalt fibres can prolong the time that concrete is eroded by salt solutions; the age of maintenance has a small effect on the mechanical and durability of the concrete; the increase in length of basalt fibres enhances the mechanical properties of the concrete, but weakens the durability. This is exacerbated by the mixing of fibres, but the increase is not significant; the effect of length on concrete resistance to mass loss, corrosion resistance factor of compressive strength, and resistance to chloride ion attack is ranked as follows: 6 mm > 12 mm > 18 mm > 6 mm + 12 mm > 6 mm + 12 mm + 18 mm. The opposite is true for effective porosity; the highest compressive strength corrosion resistance coefficient was found in the length of 6 mm, with an average increase of 6.2% compared to 18 mm, and the mixed group was generally smaller than the single mixed group. The average increase in chloride content was 25.1% for length 18 mm compared to 6 mm; the triple-doped L6-12-18 group was the largest, with an average increase of 33.9% in effective porosity over the minimum 6 mm group. Based on the data from the above indoor trials, artificial neural network models and grey cluster analysis were used to predict and analyse the data, and the prediction and categorisation results were accurate and reliable, providing a reference for subsequent studies.
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页数:17
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