Uncertainty analysis and visualization of geological subsurface and its application in metro station construction

Uncertainty analysis and visualization of geological subsurface and its application in metro station construction
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地下地质不确定性分析与可视化及其在地铁车站建设中的应用

DOI:
10.1007/s11707-021-0897-6
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发表时间:
2021-07
期刊:
Frontiers of Earth Sciences
影响因子:
--
通讯作者:
Yonghua Chen
Yonghua Chen
中科院分区:
其他
文献类型:
--
作者:
Weishen Hou;Qiaochu Yang;Xiuwen Chen;Fan Xiao;Yonghua Chen

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为了可视化和分析不确定性对地下地质的影响,提出了一种基于矢量参数的地质属性概率(GAP)方法。利用误差分布对局部数据进行扰动,首先通过蒙特卡罗模拟得到GAP等值面曲线。法矢、曲率及其熵等向量参数被用来度量等值面集合的不确定性。除了曲率和曲率熵以外的矢量参数通过将它们分布在各自的等价结构表面上或集中在初始表面上来可视化为线特征。曲率和曲率熵用彩色地图表示,揭示了扰动区域上的几何变化。利用多维尺度(MDS)方法将间隙等值面映射到低维空间中的一组点上,以获得这些等价概率面之间的总分集。地铁车站基岩地表结构的实例表明,该方法适用于地下地质不确定性的定量描述和可视化。MDS图显示了不同误差分布参数或不同分布类型引起的总分集度的差异。
To visualize and analyze the impact of uncertainty on the geological subsurface, on the term of the geological attribute probabilities (GAP), a vector parameters-based method is presented. Perturbing local data with error distribution, a GAP isosurface suite is first obtained by the Monte Carlo simulation. Several vector parameters including normal vector, curvatures and their entropy are used to measure uncertainties of the isosurface suite. The vector parameters except curvature and curvature entropy are visualized as line features by distributing them over their respective equivalent structure surfaces or concentrating on the initial surface. The curvature and curvature entropy presented with color map to reveal the geometrical variation on the perturbed zone. The multiple-dimensional scaling (MDS) method is used to map GAP isosurfaces to a set of points in low-dimensional space to obtain the total diversity among these equivalent probability surfaces. An example of a bedrock surface structure in a metro station shows that the presented method is applicable to quantitative description and visualization of uncertainties in geological subsurface. MDS plots shows differences of total diversity caused by different error distribution parameters or different distribution types.
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