| 张亦弛,吕明明,关涛,王佳俊,余佳,任炳昱.基于改进自回归流模型的坝基三维裂隙网络多参数模拟[J].水利学报,2021,52(5):565-577 |
| 基于改进自回归流模型的坝基三维裂隙网络多参数模拟 |
| Multivariate parameter simulation of 3D fracture network in dam foundation based on improved autoregressive flow model |
| 投稿时间：2020-09-07 |
| DOI：10.13243/j.cnki.slxb.20200703 |
| 中文关键词: 水电工程 坝基岩体 离散裂隙网络 多参数模拟 自回归流模型 |
| 英文关键词: hydropower engineering rock mass of dam foundation discrete fracture network multivariate parameter simulation autoregressive flow model |
| 基金项目:国家重点研发计划项目（2018YFC0406704）；国家自然科学基金雅砻江联合基金项目（U1765205）；国家自然科学基金项目（51879186） |
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| 中文摘要: |
| 在水电工程坝基三维离散裂隙网络（Discrete Fracture Network，DFN）随机建模中，关键在于对裂隙的倾向、倾角、开度等几何多参数的多维联合分布估计。然而，现有基于典型分布的DFN模拟方法存在缺乏考虑裂隙参数之间的相关性，且难以实现对裂隙参数多维联合分布的高精度概率密度估计的问题。针对上述问题，本文提出一种改进的自回归流模型——密度峰值聚类自回归流（Density Peak Clustering Autoregressive Flow，DPCAF），通过采用高斯混合分布与DensityPeak聚类算法改进标准化特征空间的基础分布，弥补自回归流在分布估计的过程中难以考虑裂隙优势分组的不足，提高对于多峰的联合分布的拟合能力；进一步提出基于DPCAF模型的裂隙网络多参数模拟方法，考虑裂隙几何参数之间的相关性，实现其多维联合分布的精确极大似然估计与采样。工程应用结果表明，DPCAF模型相比于现有基于典型分布的方法能够更好地拟合复杂的多参数联合分布，且具备能够建立裂隙几何参数关联关系的优势，从而保证了DFN模型的可靠性。 |
| 英文摘要: |
| In stochastic modeling of 3D discrete fracture network （DFN） in dam foundations，the key lies in the estimation of multidimensional joint distribution of geometric parameters of fractures including dip， dip direction， aperture etc. However， existing DFN modeling methods are based on classic distributions， which ignore the correlations among parameters and cannot realize the high precision probability density estimation of the multidimensional joint distribution of fracture parameters. To solve those problems，this paper proposes an improved autoregressive flow model——Density Peak Clustering Autoregressive Flow （DPCAF）， in which the Gaussian mixture distribution and DensityPeak clustering algorithm are used to modify the base distribution in normalized feature space. This model makes up for the deficiency of autoregressive flow which lacks consideration of fracture dominant partitioning in distribution estimation， and enhances the fitting ability to multi-modal joint distributions. Furthermore，a method of multivariate parameter simulation of 3D fracture network using DPCAF model is proposed，which takes the correlations among fracture parameters into account，and can realize the accurate maximum likelihood estimation and sampling from the multidimensional joint distribution. Engineering application shows that the DPCAF model can better fit the complex multidimensional joint distributions of fracture parameters compared with classic distribution-based methods， and have the advantage of construct the correlation structures among fracture parameters， which further ensure the reliability of DFN models. |
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