Application of the numerical manifold method for stress wave propagation across rock masses

In this paper, the numerical manifold method (NMM) is extended to study wave propagation across rock masses. First, improvements to the system equations, contact treatment, and boundary conditions of the NMM are performed, where new system equations are derived based on the Newmark assumption of the space–time relationship, the edge‐to‐edge contact treatment is further developed for the NMM to handle stress wave propagation across discontinuities, and the viscous non‐reflection boundary condition is derived based on the energy minimisation principle. After the modification, numerical comparisons between the original and improved NMM are presented. The results show that the original system equations result in artificial numerical damping, which can be overcome by the Newmark system equations. Meanwhile, the original contact scheme suffers some calculation problems when modelling stress wave propagation across a discontinuity, which can be solved by the proposed edge‐to‐edge contact scheme. Subsequently, the influence of the mesh size and time step on the improved NMM for stress wave propagation is studied. Finally, 2D wave propagation is modelled, and the model's results are in good agreement with the analytical solution. Copyright © 2013 John Wiley & Sons, Ltd.     

结合投影变换和相位相关的海冰运动监测

为提高对渤海海冰旋转和平移运动的监测精度,提出一种基于投影变换的相位相关跟踪方法。选取连续8景静止水色成像仪(GOCI)图像序列,根据特征图像窗口的投影变换构造辅助函数,通过寻求函数最优解得到旋转角度集合,选择修正相关系数确定最佳旋转角度,同时根据相位信息实现海冰样本间亚像素级别的平移跟踪,消除传统相位相关法中因忽略图像相频特性所造成的匹配误差。实验结果表明,以手动测量的旋转角度为基准,该方法和传统相位相关法的旋转监测均方根误差的最大值/平均值分别为0.59/0.50与1.41/0.94,跟踪速度提高了50.6%;海冰平移运动的速度矢量与辽东湾的现场实测数据及历史资料记录数据基本一致。该方法对渤海海冰旋转和平移运动具有较好的跟踪效果。     

Grid pattern recognition in road networks using the C4.5 algorithm

Pattern recognition in road networks can be used for different applications, including spatiotemporal data mining, automated map generalization, data matching of different levels of detail, and other important research topics. Grid patterns are a common pattern type. This paper proposes and implements a method for grid pattern recognition based on the idea of mesh classification through a supervised learning process. To train the classifier, training datasets are selected from worldwide city samples with different cultural, historical, and geographical environments. Meshes are subsequently labeled as composing or noncomposing grids by participants in an experiment, and the mesh measures are defined while accounting for the mesh’s individual characteristics and spatial context. The classifier is generated using the C4.5 algorithm. The accuracy of the classifier is evaluated using Kappa statistics and the overall rate of correctness. The average Kappa value is approximately 0.74, which corresponds to a total accuracy of 87.5%. Additionally, the rationality of the classifier is evaluated in an interpretation step. Two other existing grid pattern recognition methods were also tested on the datasets, and comparison results indicate that our approach is effective in identifying grid patterns in road networks.     

基于层区带刻度区地质特点的资源评价方法适用性分析

针对新型的层区带刻度区进行资源评价方法的适应性研究是长庆四次资评一项重要内容。采用油藏规模序列法、油藏过程模型法、容积法和饱和探井法4种资源评价方法,对具不同成藏特点的刻度区进行了深入的方法适用性分析和参数研究。研究结果表明,过程类资源评价方法对低渗透、特低渗透连续性岩性油藏,在以储量提交单元作为统计单元进行油藏发现序列与规模序列模拟时,计算参数的合理性与计算结果认知度很难达到统一。而勘探程度类资源评价方法,在深入的地质分析基础上,选择合理适宜的关键参数,是可以求得较为可信的地质资源量。当然,评价者对评价对象的认识程度和对评价方法的掌握程度也影响着资源评价的结果。