文章摘要
唐骁宇, 高文华, 张宗堂, 易梅辉, 邬 俊.基于灰色关联法的膨胀岩崩解性影响因素分析Journal of Water Resources and Water Engineering[J].,2020,31(3):240-245
基于灰色关联法的膨胀岩崩解性影响因素分析
Influencing factors of disintegration of swelling rock based on grey system correlation analysis
  
DOI:10.11705/j.issn.1672-643X.2020.03.35
中文关键词: 灰色系统关联  分形维数  膨胀岩  干湿循环  崩解
英文关键词: grey system correlation  fractal dimension  swelling rock  dry-wet cycle  disintegration
基金项目:湖南省教育厅重点科研项目(16A073); 湖南省研究生科研创新项目(CX20190790); 湖南科技大学岩土工程稳定控制与健康监测省重点实验室开放基金项目(E21807)
Author NameAffiliation
TANG Xiaoyu, GAO Wenhua, ZHANG Zongtang, YI meihui, WU Jun (湖南科技大学 岩土工程稳定控制与健康监测湖南省重点实验室 湖南 湘潭 411201) 
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中文摘要:
      膨胀岩的崩解是众多工程灾害的主要诱因,这种崩解现象的影响因素是多样的。而灰色关联分析法是用于衡量各影响因素之间联系程度的数据分析方法,其本质是以数据处理的方式求出不同影响因素间发展趋势的相异或相似程度。采用一种分形维数的计算方法求得膨胀岩崩解的分形特征,并基于灰色关联分析法,探究在不同干燥温度、初始单块质量、干湿循环次数为影响因素的情况下,对膨胀岩崩解机理的影响程度。经过灰色关联分析,得到各影响因素对膨胀岩崩解分形维数的关联度排序为初始单块质量<干燥温度<干湿循环次数。结果表明,在处理膨胀岩的过程中,干燥温度、初始单块质量、干湿循环次数等都对膨胀岩崩解产生很大影响,其中干湿循环次数的影响最大。
英文摘要:
      The disintegration of swelling rocks is the main inducement of engineering disasters, which is influenced by various factors. Grey system correlation analysis is a method of measuring the correlation between factors according to the degree of dissimilarity or similarity of the development trend. The fractal characteristics of swelling rock disintegration were obtained using the calculation method of fractal dimension. Based on the grey system correlation analysis method, the influences of different drying temperatures, different initial mass of single rock and the number of dry–wet cycles on the disintegration of swelling rocks were explored. Through grey system correlation analysis, the correlation of each influencing factor to the fractal dimension of swelling rock disintegration was ranked as the number of dry–wet cycles> the drying temperatures>the initial mass of single block. The results showed that the drying temperatures, the initial mass of single rock, and the number of dry-wet cycles affected disintegration greatly, among which the correlation degree of the number of dry-wet cycles is the greatest.
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