岩石裂隙的方向性研究
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摘要
裂隙是岩体中的软弱结构面,包括断层、节理、劈理等。裂隙等结构面对岩体的变形、强度、破坏方式和机制等力学性质的影响远大于岩石材料本身;同时裂隙等结构面还是地下水流和水流中溶质的运移的重要通道。故对岩体的裂隙等结构面的研究是把握岩体性质的重要手段。
不同位置、不同形状、不同方向、不同规模等几何特征的结构面对岩体的力学性质和渗流过程的影响也差异很大,对岩体裂隙等结构面的几何特征研究是岩体裂隙的研究重要组成部分之一。在岩体的所有几何特征中,岩体的方向性是岩体具有非均匀性、各向异性和非连续性重要原因之一。
本文主要对岩体裂隙的方向性进行研究。由于裂隙的分布范围广,现场勘测困难,数据量大,传统统计分析方法计算量大,故本文以VC++ 6.0为编程平台编写模拟程序,用计算机手段对裂隙的方向性研究。
考虑到同组裂隙形成原因、力学特征和几何特征的相似性,首先设计聚类分析算法对裂隙进行分组。同时通过编程实现玫瑰花图和等密度图绘制,对裂隙分组结果进行比较和验证。通过成图分析,三者对裂隙的统计分组结果基本相同。裂隙分组方法正确实用。
为了掌握裂隙的统计学特征,本文接下来用概率统计方法对分组的裂隙进行几种经典的分布函数拟合。拟合结果可以得到相应的分布函数的参数和方向性数据的均值,最大最小值范围。
一般说来,由于岩体中的裂隙数量非常巨大,勘测方法有限,同时为了验证上一步分布拟合的方法的正确性,本文用蒙特卡罗法产生对应拟合的参数的随机方向性数据。
最后,为验证按本文思路编制的软件FG.EXE的实用性和正确性,在软件中输入三峡水利工程左岸一区裂隙编录数据分别进行裂隙极点图绘制,裂隙分组,裂隙等密度图绘制,裂隙玫瑰花图绘制,裂隙分布函数拟合及随机方向性数据产生。
Fracture is weak structural plane of rock mass, including fault, joint, cleavage, etc. Fracture has greater influence on rock mass deformation, strength, destructive mechanism and destructive mode than rock mineral components. And it is the passage of fluid flow and solute transportation. Therefore, it is an important means of mastering rock nature to study rock fracture.
The influence is very different on mechanical properties and flow process,because of the fracture's geometric features of various location, shape, orientation and size. The study of fracture's geometric features is one of important parts in rock fracture study. Fracture orientation, among all geometric features, is one of important reasons why rock mass has heterogeneity,anisotropy and discontinuity.
The main focus of this paper is the study on rock fracture's orientation. Because of fracture wide distribution,difficulty in site investigation,large volume of data and large amount of calculation of statistical analysis in using traditional Method,this paper uses Visual C++ to program and simulate. In other words, Study fracture orientation by means of computers.
Considering that fracture forming reason, mechanical characteristics and geometric features are similar in the same group, first, fractures is grouped by cluster analysis. Then, by programming realization, rose diagram and density contour are drawn to compare and validate the result of fracture grouping. It shows that the results of three statistical analysis methods are almost same. And the method of fractures grouping is right and reliable.
In order to obtained Statistics characteristics, the next step is to fit distribution function parameters for fractures grouped. After Fitting, distribution function parameters values、mean values、maximum and minimum can be obtained.
On account of large quantity of fractures in rock mass and limitation of Exploration Method, and to prove the correctness of fitting step, this paper use Monte-Carlo method to generate random data of fractures orientation. The data accords with the Fitted parameters of last step.
At last, in order to test FG.EXE's practicality, which is developed according to above research results, it is applied in the fractures orientation data of three Gorges dam base's left bank. The progress is draw fractures plot graph, fractures grouping, density contour, rose diagram and distribution parameters fitting and random data generation.
不同位置、不同形状、不同方向、不同规模等几何特征的结构面对岩体的力学性质和渗流过程的影响也差异很大,对岩体裂隙等结构面的几何特征研究是岩体裂隙的研究重要组成部分之一。在岩体的所有几何特征中,岩体的方向性是岩体具有非均匀性、各向异性和非连续性重要原因之一。
本文主要对岩体裂隙的方向性进行研究。由于裂隙的分布范围广,现场勘测困难,数据量大,传统统计分析方法计算量大,故本文以VC++ 6.0为编程平台编写模拟程序,用计算机手段对裂隙的方向性研究。
考虑到同组裂隙形成原因、力学特征和几何特征的相似性,首先设计聚类分析算法对裂隙进行分组。同时通过编程实现玫瑰花图和等密度图绘制,对裂隙分组结果进行比较和验证。通过成图分析,三者对裂隙的统计分组结果基本相同。裂隙分组方法正确实用。
为了掌握裂隙的统计学特征,本文接下来用概率统计方法对分组的裂隙进行几种经典的分布函数拟合。拟合结果可以得到相应的分布函数的参数和方向性数据的均值,最大最小值范围。
一般说来,由于岩体中的裂隙数量非常巨大,勘测方法有限,同时为了验证上一步分布拟合的方法的正确性,本文用蒙特卡罗法产生对应拟合的参数的随机方向性数据。
最后,为验证按本文思路编制的软件FG.EXE的实用性和正确性,在软件中输入三峡水利工程左岸一区裂隙编录数据分别进行裂隙极点图绘制,裂隙分组,裂隙等密度图绘制,裂隙玫瑰花图绘制,裂隙分布函数拟合及随机方向性数据产生。
Fracture is weak structural plane of rock mass, including fault, joint, cleavage, etc. Fracture has greater influence on rock mass deformation, strength, destructive mechanism and destructive mode than rock mineral components. And it is the passage of fluid flow and solute transportation. Therefore, it is an important means of mastering rock nature to study rock fracture.
The influence is very different on mechanical properties and flow process,because of the fracture's geometric features of various location, shape, orientation and size. The study of fracture's geometric features is one of important parts in rock fracture study. Fracture orientation, among all geometric features, is one of important reasons why rock mass has heterogeneity,anisotropy and discontinuity.
The main focus of this paper is the study on rock fracture's orientation. Because of fracture wide distribution,difficulty in site investigation,large volume of data and large amount of calculation of statistical analysis in using traditional Method,this paper uses Visual C++ to program and simulate. In other words, Study fracture orientation by means of computers.
Considering that fracture forming reason, mechanical characteristics and geometric features are similar in the same group, first, fractures is grouped by cluster analysis. Then, by programming realization, rose diagram and density contour are drawn to compare and validate the result of fracture grouping. It shows that the results of three statistical analysis methods are almost same. And the method of fractures grouping is right and reliable.
In order to obtained Statistics characteristics, the next step is to fit distribution function parameters for fractures grouped. After Fitting, distribution function parameters values、mean values、maximum and minimum can be obtained.
On account of large quantity of fractures in rock mass and limitation of Exploration Method, and to prove the correctness of fitting step, this paper use Monte-Carlo method to generate random data of fractures orientation. The data accords with the Fitted parameters of last step.
At last, in order to test FG.EXE's practicality, which is developed according to above research results, it is applied in the fractures orientation data of three Gorges dam base's left bank. The progress is draw fractures plot graph, fractures grouping, density contour, rose diagram and distribution parameters fitting and random data generation.
引文
[1]杜时贵.岩体结构面的工程性质.北京:地震出版社,2000
[2]黄润秋.复杂岩体结构精细描述及其工程应用.北京:科学出版社,2004
[3] Mardia, K. V. Statistics of Directional Data. London: Academic Press Inc,1972
[4] Gaziev Eq TidenEN. Probabilities Approach to the Study jointing in Rock Masses. Bulletin of Ini.Assoe.of Engineering Geology,1979, 20~22
[5] Miller S M,Borgman L E.Spectral Tyepe Simulation of Spatially Correlated Fracture Set Properties.Mathematical Geology,1985,17:12~34
[6] Snow D T. The Freqency and Apertures of Fracture in Rock. Int .J.of Rock Mechanics and Ming Science,1970,7(1):23~40
[7] Cruden D M.Discribing the Size of Discontinuities. Int.J.of Rock Mechanics and Ming Science,1977,14(3):23~40
[8] Priest S D,Hudson J A. Estimation of Discontinuity S pacing and Trace Length Using Scanline. Int. J. Rock Mech. Min. Sci. and Geomech,Abstr,1981,21(4):204~212
[9]B.Amadei&S.Saeb Constitutive Models of rock joints. Rock Joint,Barton&Stephansson(1990)
[10]齐曲.裂隙岩体的随机分析方法:[硕士论文].北京:北京交通大学2006
[11] Priest S D,Hudson J A. Discontinuity spacing in rock. International Journal of Rock Mechanics and Mining Sciences,13:135~148,1976
[12]金曲生,王思敬.估计迹长概述分布函数的新方法及其应用.工程地质学报,1997,5(2):15~155
[13]金曲生,范建军.结构面密度计算法及其应用.岩石力学与工程学报,1998,17 (3):273~278
[14] Qingchun Yu. Analyses for Fluid Flow and Solute Transport in Discrete Fracture Network:[Ph.D.thesis],the Graduate School of Engineering, Kyoto University,2000
[15]朱志澄.构造地质学.武汉:中国地质大学出版社,1999
[16]陈良维.数据挖掘中聚类算法研究.微计算机信息, 2006(22)7 1~2
[17]张丽芳.聚类方法及应用研究:[硕士学位论文].广州:中山大学,2006
[18]陆璇.应用统计.北京:清华大学出版社,1999: 2~15
[19]梅长林.实用统计方法.北京:科学出版社, 2002: 117~130
[20] Nelder J A, Mead R. A simplex method for function minimization. Computer J, 1965, 7: 308~313
[21]徐开礼.构造地质学.北京:地质出版社,1989:121~125
[22]杨继清.关于岩体结构网络模拟的计算机辅助研究:[硕士论文].云南:昆明理工大学,2005
[23]王靖波,潘愚,张绪定.基于Kriging方法的空间散乱点插值.计算机辅助设计与图形学学报,1999,11(6):525~529
[24]王家华,高海余,周叶.克里金地质绘图技术的计算机的模型和算法.北京:石油工业出版社.1999:150~154
[25]张仁铎.空间变异理论及应用.北京:科学出版社,2005:18~28
[26] LamN5.Spatial interpolation methods: a review. The American Cartographer, 1983,10(2):129~149
[27]李国庆,马凤山,邓清海等.计算机绘制节理等密度图的原理和方法.物探化探计算技术2008,30(1):81~83
[28]余淳梅,周继彬.节理等密图的计算机化.世界地质,2002,21(1):9~10
[29]王家华,高海余,周叶.克里金地质绘图技术.北京:石油工业出版社, 1999:255~258
[30]徐钟济.蒙特卡罗方法.上海:上海科学技术出版社,1985:2~25
[31]何思谦.数学辞海,第四卷.北京:中国科学技术出版社2002:103~107
[32]方在根.计算机模拟和蒙特卡洛方法.北京:北京工业出版社,1988:1~10
[33]花嵘,傅游,康继昌.直接模拟蒙特卡洛问题的并行化方法.计算机工程,2004, 30(5):40~41
[34]尹增谦,管景峰,张晓宏等.蒙特卡罗方法及应用.物理与工程,2002,3:45—49
[35]袁贵星,王平.蒙特卡洛模拟及其在公差设计中的应用.天津科技大学学报,2008,23(2):62~64
[36]奚春雷.岩体节理数据的概率统计:[硕士学位论文].沈阳:东北大学,2003
[37]高慧璇.统计计算.北京:北京大学出版社,1995:30~13
[38]裴鹿成,张孝泽.蒙特卡罗方法及其在粒子输运问题中的应用.北京:科学出版社,1980:5~10
[39]王萍,许海洋.一种新的随机数组合发生器的研究.计算机技术与发展,16(4),2006:79~81
[40] Tausworthe, R. C. Random number generated by linear recurrence modulo two. Math. Comput,19,1965:201~209
[41]于青春,薛果夫,陈德基.裂隙岩体一般块体理论.北京:中国水利水电出版社,2007:66~77
[42]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社,2001:83~86
[43]肖春来,柴文义,章月.基于经验分布的条件Var计算方法研究.数理统计与管理,25(5) 2005:92~93
[44]冯自霞.三峡坝基岩体裂隙统计及三维建模:[硕士学位论文].北京:中国地质大学.2008
[45]陈德基.长江三峡工程地质研究综述.人民长江,34(8),2003:16~19
[2]黄润秋.复杂岩体结构精细描述及其工程应用.北京:科学出版社,2004
[3] Mardia, K. V. Statistics of Directional Data. London: Academic Press Inc,1972
[4] Gaziev Eq TidenEN. Probabilities Approach to the Study jointing in Rock Masses. Bulletin of Ini.Assoe.of Engineering Geology,1979, 20~22
[5] Miller S M,Borgman L E.Spectral Tyepe Simulation of Spatially Correlated Fracture Set Properties.Mathematical Geology,1985,17:12~34
[6] Snow D T. The Freqency and Apertures of Fracture in Rock. Int .J.of Rock Mechanics and Ming Science,1970,7(1):23~40
[7] Cruden D M.Discribing the Size of Discontinuities. Int.J.of Rock Mechanics and Ming Science,1977,14(3):23~40
[8] Priest S D,Hudson J A. Estimation of Discontinuity S pacing and Trace Length Using Scanline. Int. J. Rock Mech. Min. Sci. and Geomech,Abstr,1981,21(4):204~212
[9]B.Amadei&S.Saeb Constitutive Models of rock joints. Rock Joint,Barton&Stephansson(1990)
[10]齐曲.裂隙岩体的随机分析方法:[硕士论文].北京:北京交通大学2006
[11] Priest S D,Hudson J A. Discontinuity spacing in rock. International Journal of Rock Mechanics and Mining Sciences,13:135~148,1976
[12]金曲生,王思敬.估计迹长概述分布函数的新方法及其应用.工程地质学报,1997,5(2):15~155
[13]金曲生,范建军.结构面密度计算法及其应用.岩石力学与工程学报,1998,17 (3):273~278
[14] Qingchun Yu. Analyses for Fluid Flow and Solute Transport in Discrete Fracture Network:[Ph.D.thesis],the Graduate School of Engineering, Kyoto University,2000
[15]朱志澄.构造地质学.武汉:中国地质大学出版社,1999
[16]陈良维.数据挖掘中聚类算法研究.微计算机信息, 2006(22)7 1~2
[17]张丽芳.聚类方法及应用研究:[硕士学位论文].广州:中山大学,2006
[18]陆璇.应用统计.北京:清华大学出版社,1999: 2~15
[19]梅长林.实用统计方法.北京:科学出版社, 2002: 117~130
[20] Nelder J A, Mead R. A simplex method for function minimization. Computer J, 1965, 7: 308~313
[21]徐开礼.构造地质学.北京:地质出版社,1989:121~125
[22]杨继清.关于岩体结构网络模拟的计算机辅助研究:[硕士论文].云南:昆明理工大学,2005
[23]王靖波,潘愚,张绪定.基于Kriging方法的空间散乱点插值.计算机辅助设计与图形学学报,1999,11(6):525~529
[24]王家华,高海余,周叶.克里金地质绘图技术的计算机的模型和算法.北京:石油工业出版社.1999:150~154
[25]张仁铎.空间变异理论及应用.北京:科学出版社,2005:18~28
[26] LamN5.Spatial interpolation methods: a review. The American Cartographer, 1983,10(2):129~149
[27]李国庆,马凤山,邓清海等.计算机绘制节理等密度图的原理和方法.物探化探计算技术2008,30(1):81~83
[28]余淳梅,周继彬.节理等密图的计算机化.世界地质,2002,21(1):9~10
[29]王家华,高海余,周叶.克里金地质绘图技术.北京:石油工业出版社, 1999:255~258
[30]徐钟济.蒙特卡罗方法.上海:上海科学技术出版社,1985:2~25
[31]何思谦.数学辞海,第四卷.北京:中国科学技术出版社2002:103~107
[32]方在根.计算机模拟和蒙特卡洛方法.北京:北京工业出版社,1988:1~10
[33]花嵘,傅游,康继昌.直接模拟蒙特卡洛问题的并行化方法.计算机工程,2004, 30(5):40~41
[34]尹增谦,管景峰,张晓宏等.蒙特卡罗方法及应用.物理与工程,2002,3:45—49
[35]袁贵星,王平.蒙特卡洛模拟及其在公差设计中的应用.天津科技大学学报,2008,23(2):62~64
[36]奚春雷.岩体节理数据的概率统计:[硕士学位论文].沈阳:东北大学,2003
[37]高慧璇.统计计算.北京:北京大学出版社,1995:30~13
[38]裴鹿成,张孝泽.蒙特卡罗方法及其在粒子输运问题中的应用.北京:科学出版社,1980:5~10
[39]王萍,许海洋.一种新的随机数组合发生器的研究.计算机技术与发展,16(4),2006:79~81
[40] Tausworthe, R. C. Random number generated by linear recurrence modulo two. Math. Comput,19,1965:201~209
[41]于青春,薛果夫,陈德基.裂隙岩体一般块体理论.北京:中国水利水电出版社,2007:66~77
[42]盛骤,谢式千,潘承毅.概率论与数理统计.北京:高等教育出版社,2001:83~86
[43]肖春来,柴文义,章月.基于经验分布的条件Var计算方法研究.数理统计与管理,25(5) 2005:92~93
[44]冯自霞.三峡坝基岩体裂隙统计及三维建模:[硕士学位论文].北京:中国地质大学.2008
[45]陈德基.长江三峡工程地质研究综述.人民长江,34(8),2003:16~19
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