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| Characterization and modeling of anisotropic random field of soil parameters |
| Received:February 19, 2020 Revised:July 22, 2020 |
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| DOI：10.7511/jslx20200219001 |
| KeyWord:random field anisotropy parameter inversion matrix decomposition |
| Author | Institution |
| 王占盛 |
中铁二院工程集团有限责任公司, 成都 |
| 陈健 |
中国科学院武汉岩土力学研究所, 武汉 |
| 戎虎仁 |
山西大学 土木工程系, 太原 |
| 杨定强 |
中铁第六勘察设计院集团有限公司, 天津 |
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| Abstract: |
| The spatial correlation of soil parameters is anisotropic,so the research on modeling methods of an anisotropic random field is of great significance.In this paper,firstly,by analyzing the correlation function,the problem of anisotropic correlation is reduced to the discussion of correlation distance function,and then a method to describe the anisotropic correlation of parameters is given.Secondly,the problems faced by two kinds of random field inversion methods in dealing with anisotropic problems are analyzed:(1) the local average partition method is only suitable for the generation of transversely isotropy random fields.It is difficult to deal with arbitrary anisotropic problems.(2) When matrix decomposition method is used to invert a random field,the grid number of the random field will be limited by the computing power of the computer,so it is difficult to deal with a large-scale random field inversion.Aiming at solving the above two problems,this paper improves the matrix decomposition method based on the fast attenuation characteristics of correlation function,and compares the inversion accuracy of the improved matrix decomposition method with the local average division method.At the same time,the improved matrix decomposition method is used to invert the rotational transversal isotropic random field.The results show that the improved matrix decomposition method is applicable to the anisotropic random field problem. |
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