Stress distribution characteristic analysis and control of coal and gas outburst disaster in a pressure-relief boundary area in protective layer mining

Coal and gas outburst disasters in coal seams are becoming more serious as coal mines extend deeper underground in China. Furthermore, the protective coal seam mining technology featured by economic efficiency has been proven to be the most effective and widely applied method for the prevention of coal and gas outburst disasters. However, the determinations of the protective area coal and gas outburst prevention in a pressure-relief boundary area are fundamental issues that research should be focused on. The technical method for determining stress distribution in pressure-relief boundary area during protective coal seam mining is put forward in this paper. The method is based on a stress-seepage coupled relationship within a gas-containing coal seam. The method includes complex lab experiments and on-site measurements at the Qingdong Coal Mine. The final data illustrate that the permeability and vertical stress in the pressure-relief boundary area of the coal sample form a negative exponential function relationship. Additionally, the permeability of the coal sample within the abovementioned area is significantly different compared with that located at the center of the pressure-relief area. In the pressure-relief boundary area, the gas pressure distribution gradient is 0.0375 MPa/m, while the vertical stress distribution gradient registers 0.56 MPa/m. Under this condition, coal and gas outburst disasters are prone to be triggered. Therefore, effective precautions against coal and gas outburst disasters can be put forward in accordance with stress distribution characteristics within the abovementioned “boundary area.”     

川南沐川地区宣威组底部铌-稀土多金属富集层富集规律、沉积环境与成矿模式

云南、贵州地区对晚二叠世宣威组底部Nb-REE多金属富集层的研究取得了重要进展,但其成因还有较大争议.为厘清沐川地区宣威组底部Nb-REE多金属富集层成因机制及富集规律,本研究开展了野外实地调查、矿物学、岩相古地理与岩石地球化学等系统性研究,探讨其物源、富集规律,建立了成矿模式.结果 表明,川南沐川地区宣威组底部Nb-...     

维嘉海山沉积过程及其对西太平洋海山演化的意义

海山沉积过程与全球气候变化和古海洋演化有着紧密联系,维嘉海山保留了西太平洋晚中生代以来的完整沉积记录,是探索西太平洋海山构造演化的理想场所.基于浅地层剖面、大洋钻探和最新相关研究成果,通过研究海山的沉积特征、火山活动和沉降速率等,探索西太平洋维嘉海山晚中生代以来的沉积过程.结果显示维嘉海山顶部发育3个沉积单元,并发现了...     

基于图形处理器的伪谱和高阶有限 差分混合方法地震波数值模拟

伪谱和高阶有限差分混合方法, 在垂直方向采用交错网格有限差分算子, 利用其并行程度高的特点, 在水平方向采用伪谱算子, 保留其高精度的优势, 是计算地震波场的有效方法. 图形处理器(graphic processing unit, 简写为GPU) 由于其高度并行性, 在计算此类问题中有显著的优势. 由英伟达(NVIDIA)公司推出的统一计算设备架构(compute unified device architecture, 简写为CUDA)平台极大地简化了GPU编程的难度. 为提高计算效率, 本文实现了基于CUDA 平台的混合方法二维地震波场模拟. 然后基于二维均匀介质模型将CPU与GPU版本的运行时间进行对比. 实际测试结果表明, 基于CUDA 的并行模拟方法在保证计算精度的同时显著地提高了计算速度, 为开展大规模非均匀地球介质地震波传播数值模拟提供了一种可选的方法.      

北京城市休闲商务区的时空分布特征与成因

城市休闲商务区（Recreational Business District, RBD）作为城市重要的游憩空间,为外来游客和城市居民提供休闲消费的场所,逐渐受到学界和业界重视。目前大多数研究还停留在概念层面,在分类、空间结构、分布规律、分异成因等方面上还缺乏一定的实证和定量研究。结合前人研究经验,重新定义RBD,并依据城市RBD的特征和属性将其分为大型购物中心、休闲商业街、城市休闲区三类。选取1990年、2000年、2014年三个时间截面对北京各类城市RBD点进行统计,采用基尼系数、空间插值、核密度分析、地理探测器等方法,结合ArcGIS软件,对北京城市RBD的时空分布特征和成因进行分析,得出以下结论：① 时序上看,北京城市RBD的数量和规模不断增加,增速变快,不同类型的RBD出现不同幅度的空间扩张;② 北京城市RBD的空间集聚程度不断加强,不同类型的RBD,存在一定的增幅和增速差异;③ 北京城市RBD的整体空间结构呈“单核聚集—双核发展—网状扩散”的发展模式;④ 城市RBD多选址在交通便利、临近旅游景区、居民和游客密度较高、地价相对较高的地区。⑤ 游客密度对各类型的城市RBD规模均有较大影响;对于不同类型的城市RBD,各因素对其规模的影响也有所不同。     

基于A-T-R的旅游小城镇分类、评价与发展模式研究

在科学界定旅游小城镇基础上,梳理旅游小城镇的分类标准,确立一类基于核心吸引物（A）—小镇（T）—乡村环境（R）的新分类方法,将旅游小城镇分为AT一体、AT分离、A+T+R联动与ATR创意再造4种类型。结合旅游小城镇发展中的实际状态,依据A、T、R三类初始条件不同组合情况提炼出六大旅游小城镇的发展模式,为旅游小城镇深层次研究提供参考和依据,进一步推动旅游小城镇的健康发展。     

鄂尔多斯市2005-2014年地下水位变化

鄂尔多斯市地处半干旱区,水资源缺乏,监测地下水位的变化对于地区生态和经济发展具有重要意义。本研究利用鄂尔多斯市6个地下水位监测井2005-2014年的监测资料,分析了该地区地下水位变化特征。结果显示:(1)本地区地下水位2005-2006年有所下降,2007-2010年逐年抬升,2011年受严重干旱影响,地下水位为近10年来最低值,从2012年开始至2014年,以每年0.14 m的幅度抬升,2014年为近10年最高值,地下水位的年际变化主要与煤炭开采和经济发展有关。(2)地下水位的年内季节变化明显,与降雨量、蒸发量和农业灌溉用水的相关性较高。3-7月,水位持续下降,7月地下水位为年内最低点;8-10月,水位逐步回升;11月至次年2月水位总体呈略微抬升状态,次年2月为年内最高值。     

水土流失区马尾松林植被提取的土壤调节指数分析

为实现水土流失区植被遥感信息的准确提取,本文采用2007年ALOS 10 m多光谱影像,利用土壤调节植被指数SAVI和MSAVI,对福建长汀水土流失区马尾松林不同植被覆盖密度的3个实验区进行植被提取,并选用不同的土壤调节因子（L=0.25,0.5,0.75,1）做实验,将结果和以NDVI植被指数提取的结果进行对比,分析了提取效果及受土壤噪音的影响程度。实验表明,SAVI指数能提高水土流失区的植被提取精度。在中、低植被覆盖区,其提取的总精度比NDVI高出2%~7%,Kappa系数高出7%~18%;而土壤调节因子L的取值对植被信息的提取也呈现出一定的规律性,即：随着L从0向1递增,SAVI提取稀疏植被的能力上升而探测阴坡植被的能力下降。总体来看,对于低植被覆盖和中等植被覆盖地区,可分别用SAVI（L取0.75）和SAVI（L取0.5）来提取植被信息,对于高植被覆盖区,仍可直接用NDVI进行植被信息提取;研究发现MSAVI在植被信息提取中并不具有特别的优势。     

Changes of soil surface roughness under water erosion process

The objective of this study was to determine the changing characteristics of soil surface roughness under different rainfall intensities and examine the interaction between soil surface roughness and different water erosion processes. Four artificial management practices (raking cropland, artificial hoeing, artificial digging, and contour tillage) were used according to the local agriculture customs of the Loess Plateau of China to simulate different types of soil surface roughness, using an additional smooth slope for comparison purposes. A total of 20 rainfall simulation experiments were conducted in five 1 m by 2 m boxes under two rainfall intensities (0.68 and 1.50 mm min^?1) on a 15° slope. During splash erosion, soil surface roughness decreased in all treatments except raking cropland and smooth baseline under rainfall intensity of 0.68 mm min^?1, while increasing for all treatments except smooth baseline under rainfall intensity of 1.50 mm min^?1. During sheet erosion, soil surface roughness decreased for all treatments except hoeing cropland under rainfall intensity of 0.68 mm min^?1. However, soil surface roughness increased for the artificial hoeing and raking cropland under rainfall intensity of 1.50 mm min^?1. Soil surface roughness has a control effect on sheet erosion for different treatments under two rainfall intensities. For rill erosion, soil surface roughness increased for raking cropland and artificial hoeing treatments, and soil surface roughness decreased for artificial digging and the contour tillage treatments under two rainfall intensities. Under rainfall intensity of 0.68 mm min^?1, the critical soil surface roughness was 0.706 cm for the resistance control of runoff and sediment yield. Under rainfall intensity of 1.50 mm min^?1, the critical soil surface roughness was 1.633 cm for the resistance control of runoff, while the critical soil surface roughness was 0.706 cm for the resistance control of sediment yield. These findings have important implications for clarifying the erosive nature of soil surface roughness and harnessing sloped farmland. Copyright © 2013 John Wiley & Sons, Ltd.