饱和砂土地震液化判别的可拓聚类预测方法
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摘要
基于可拓学的物元模型和聚类分析原理,提出了饱和砂土地震液化判别的可拓聚类方法。选取地震烈度、震中距、砂层埋置深度、地下水位、标贯击数、平均粒径、不均匀系数和动剪应力比等8个影响因素,作为饱和砂土地震液化的评价因子,构建了经典域物元和节域物元。应用物元理论和可拓集合中的关联函数,建立预测模型,通过聚类分析得到饱和砂土地震液化的判别结果。实例研究表明,该模型能客观地反映砂土的液化规律,可拓聚类预测方法应用于饱和砂土地震液化判别是有效可行的。
Based on matter-element model and the classified analysis theory, an extension clustering prediction method for assessment of seismic liquefaction of saturated sandy soil is proposed. In the method, Eight influence factors on seismic liquefaction, including seismic intensity, epicenter distance, the depth of sand, groundwater level, the blow counts of standard penetration test, mean diameter, coefficient of uniformity, cyclic shear stress ratio, are adopted to establish the classical and limited matter elements, and the dependent function of matter-element and extension set is applied to establish prediction model for seismic liquefaction of saturated sandy soil. The prediction results of the grades of seismic liquefaction of saturated sandy soil can be obtained by means of clustering analysis. The results show that this model can reflect the liquefaction potential of saturated sand objectively and truly; therefore, the extension clustering prediction method is effective and feasible in evaluation of seismic liquefaction of saturated sandy soil.
Based on matter-element model and the classified analysis theory, an extension clustering prediction method for assessment of seismic liquefaction of saturated sandy soil is proposed. In the method, Eight influence factors on seismic liquefaction, including seismic intensity, epicenter distance, the depth of sand, groundwater level, the blow counts of standard penetration test, mean diameter, coefficient of uniformity, cyclic shear stress ratio, are adopted to establish the classical and limited matter elements, and the dependent function of matter-element and extension set is applied to establish prediction model for seismic liquefaction of saturated sandy soil. The prediction results of the grades of seismic liquefaction of saturated sandy soil can be obtained by means of clustering analysis. The results show that this model can reflect the liquefaction potential of saturated sand objectively and truly; therefore, the extension clustering prediction method is effective and feasible in evaluation of seismic liquefaction of saturated sandy soil.
引文
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[2]刘勇健.基于聚类-二叉树支持向量机的砂土液化预测模型[J].岩土力学,2008,29(10):2764-2768.LIU Yong-jian.Multi-class support vectors machines model for predicting sand liquefaction based on clustering binary decision-binary tree[J].Rock and Soil Mechanics,2008,29(10):2764-2768.
[3]刘红军,薛新华.砂土地震液化预测的人工神经网络模型[J].岩土力学,2004,25(12):1942-1950.LIU Hong-jun,XUE Xin-hu.Artificial neural network model for prediction of seismic liquefaction of sand soil[J].Rock and Soil Mechanics,2004,25(12):1942-1950.
[4]夏建中,罗战友,龚晓南,等.基于支持向量机的砂土液化预测模型[J].岩石力学与工程学报,2005,24(22):4139-4144.XIA Jian-zhong,LUO Zhan-you,GONG Xiao-nan,et al.Support vector machine model for predicting liquefaction[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(22):4139-4144.
[5]余跃心.砂土液化判别方法可靠性评价[J].岩土力学,2004,25(5):803-807.SHE Yue-xin.Probability evaluation of liquefaction distinguishing method of sands[J].Rock and Soil Mechanics,2004,25(5):803-807.
[6]赵艳林,杨绿峰.砂土液化灰色综合评判[J].自然灾害学报,2000,9(1):74-79.ZHAO Yan-1in,YANG Lu-feng.Grey synthetical evaluation of liquefaction of sands[J].Journal of Natural Disasters,2000,9(1):74-79.
[7]蒋小军,严学新.可拓学理论在工程地质评价中的应用[J].上海地质,2007,101(1):45-49.JIANG Xiao-jun,YAN Xue-xin.Application of extenics theory to evaluation of engineering geologic condition[J].Shanghai Geology,2007,101(1):45-49.
[8]蔡文.物元模型及其应用[M].北京:科学文献技术出版社,1994.
[9]匡乐红,徐林荣,刘宝琛.地质灾害危险性评价指标规范化方法研究[J].铁道科学与工程学报,2007,4(1):39-43.KUANG Le-hong,XU Ling-rang,LIU Bao-chen.Research on the normalization method of risk evaluation indexes of geological hazard[J].Journal of Railway Science and Engineering,2007,4(1):39-43.
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