Study and Neural Network Analysis on Durability of Basalt Fibre Concrete
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 sho...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/6/1016 |
| _version_ | 1797608623354937344 |
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| author | Shanqing Shao Ran Wang Aimin Gong Ruijun Li Jing Xu Fulai Wang Feipeng Liu |
| author_facet | Shanqing Shao Ran Wang Aimin Gong Ruijun Li Jing Xu Fulai Wang Feipeng Liu |
| author_sort | Shanqing Shao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T05:45:48Z |
| format | Article |
| id | doaj.art-722bf96d7cd546a185a8e2a54c7bfe2c |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T05:45:48Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-722bf96d7cd546a185a8e2a54c7bfe2c2023-11-17T14:25:11ZengMDPI AGWater2073-44412023-03-01156101610.3390/w15061016Study and Neural Network Analysis on Durability of Basalt Fibre ConcreteShanqing Shao 0Ran Wang1Aimin Gong2Ruijun Li3Jing Xu4Fulai Wang5Feipeng Liu6College of Water Conservancy, Yunnan Agricultural University, Kunming 650201, ChinaCollege of Water Conservancy, Yunnan Agricultural University, Kunming 650201, ChinaCollege of Water Conservancy, Yunnan Agricultural University, Kunming 650201, ChinaHubei Academy of Water Resources and Hydropower Sciences, No. 286 Luoshi South Road, Hongshan District, Wuhan 430070, ChinaInstitute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, ChinaCollege of Water Conservancy, Yunnan Agricultural University, Kunming 650201, ChinaInstitute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, ChinaIn 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.https://www.mdpi.com/2073-4441/15/6/1016basalt fibresdurabilityartificial neural networksgrey cluster analysis |
| spellingShingle | Shanqing Shao Ran Wang Aimin Gong Ruijun Li Jing Xu Fulai Wang Feipeng Liu Study and Neural Network Analysis on Durability of Basalt Fibre Concrete Water basalt fibres durability artificial neural networks grey cluster analysis |
| title | Study and Neural Network Analysis on Durability of Basalt Fibre Concrete |
| title_full | Study and Neural Network Analysis on Durability of Basalt Fibre Concrete |
| title_fullStr | Study and Neural Network Analysis on Durability of Basalt Fibre Concrete |
| title_full_unstemmed | Study and Neural Network Analysis on Durability of Basalt Fibre Concrete |
| title_short | Study and Neural Network Analysis on Durability of Basalt Fibre Concrete |
| title_sort | study and neural network analysis on durability of basalt fibre concrete |
| topic | basalt fibres durability artificial neural networks grey cluster analysis |
| url | https://www.mdpi.com/2073-4441/15/6/1016 |
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