分层开采工艺对地表沉降的影响研究

分层开采是厚煤开采的经典工艺,这种工艺对地表沉降的影响比较复杂。通过测试原岩物理力学参数,利用有限元软件flac3D对分层和一次采全高时地表沉降进行了数值模拟。结果表明,如果采高较小,砌体梁距煤层较近,且采完上分层后长时间停采,给顶板再生留足时间,分层开采较一次采全高对地表沉降影响要小。     

Soil and vegetation carbon stocks in Brazilian Western Amazonia: relationships and ecological implications for natural landscapes

The relationships between soils attributes, soil carbon stocks and vegetation carbon stocks are poorly know in Amazonia, even at regional scale. In this paper, we used the large and reliable soil database from Western Amazonia obtained from the RADAMBRASIL project and recent estimates of vegetation biomass to investigate some environmental relationships, quantifying C stocks of intact ecosystem in Western Amazonia. The results allowed separating the western Amazonia into 6 sectors, called pedo-zones: Roraima, Rio Negro Basin, Tertiary Plateaux of the Amazon, Javari-Juruá-Purus lowland, Acre Basin and Rondonia uplands. The highest C stock for the whole soil is observed in the Acre and in the Rio Negro sectors. In the former, this is due to the high nutrient status and high clay activity, whereas in the latter, it is attributed to a downward carbon movement attributed to widespread podzolization and arenization, forming spodic horizons. The youthful nature of shallow soils of the Javari-Juruá-Purus lowlands, associated with high Al, results in a high phytomass C/soil C ratio. A similar trend was observed for the shallow soils from the Roraima and Rondonia highlands. A consistent east–west decline in biomass carbon in the Rio Negro Basin sector is associated with increasing rainfall and higher sand amounts. It is related to lesser C protection and greater C loss of sandy soils, subjected to active chemical leaching and widespread podzolization. Also, these soils possess lower cation exchangeable capacity and lower water retention capacity. Zones where deeply weathered Latosols dominate have a overall pattern of high C sequestration, and greater than the shallower soils from the upper Amazon, west of Madeira and Negro rivers. This was attributed to deeper incorporation of carbon in these clayey and highly pedo-bioturbated soils. The results highlight the urgent need for refining soil data at an appropriate scale for C stocks calculations purposes in Amazonia. There is a risk of misinterpreting C stocks in Amazonia when such great pedological variability is not taken into account.     

Effects of bed materials on the performance of an anaerobic sequencing batch biofilm reactor treating domestic sewage

The objective of this study was to determine the best performance of an anaerobic sequencing batch biofilm reactor (AnSBBR) based on the use of four different bed materials as support for biomass immobilization. The bed materials utilized were polyurethane foam (PU), vegetal carbon (VC), synthetic pumice (SP), and recycled low-density polyethylene (PE). The AnSBBR, with a total volume of 7.2L, was operated in 8-h batch cycles over 10 months, and fed with domestic sewage with an average influent chemical oxygen demand (COD) of 358+/-110mg/L. The average effluent COD values were 121+/-31, 208+/-54, 233+/-52, and 227+/-51mg/L, for PU, VC, SP, and PE, respectively. A modified first-order kinetic model was adjusted to temporal profiles of COD during a batch cycle, and the apparent kinetic constants were 0.52+/-0.05, 0.37+/-0.05, 0.80+/-0.04, and 0.30+/-0.02h(-1) for PU, VC, SP, and PE, respectively. Specific substrate utilization rates of 1.08, 0.11, and 0.86mg COD/mgVS day were obtained for PU, VC, and PE, respectively. Although SP yielded the highest kinetic coefficient, PU was considered the best support, since SP presented loss of chemical constituents during the reactor's operational phase. In addition, findings on the microbial community were associated with the reactor's performance data. Although PE did not show a satisfactory performance, an interesting microbial diversity was found on its surface. Based on the morphology and denaturing gradient gel electrophoresis (DGGE) results, PE showed the best capacity for promoting the attachment of methanogenic organisms, and is therefore a material that merits further analysis. PU was considered the most suitable material showing the best performance in terms of efficiency of solids and COD removal.     

人工神经网络在预测深基坑周边地表沉降变形中的应用研究

深基坑开挖引起的周边地表变形预测是一个复杂非线性问题,引起地表沉降的影响因素很多,各因素之间呈高度的非线性关系。传统的基坑用边地表沉降变形预测方法存在着一定的局限性,其预测精度有待提高,而人工神经网络是一种多元非线性动力学系统,可以灵活方便地对多成因的复杂未知系统进行高度建模,实现全面考虑各种主要影响因素的深基坑周边地表沉降变形预测。本文介绍了误差反向传播(BP)网络模型的结构、学习过程及其算法的改进,径向基函数(RBF)网络模型的结构及其学习过程;分析了影响深基坑开挖周边土体沉降变形的主要影响因素;以25个基坑工程的地表沉降实测资料为训练样本,建立了11个输入影响因素的BP神经网络模型和RBF神经网络模型,通过对样本的学习训练过程及对5个检验样本的预测精度,说明了人工神经网络用于预测基坑周边地表沉降的可行性和准确性。     

汶川地震灾区过渡房安置点场地选择中的地震问题

大地震后,如何在最短的时间内在灾区选择比较安全的过渡房安置点建设场地,是一项具有挑战性的工作。本文以四川省汶川8.0级大地震后灾区群众快速安置为背景,论述了选择过渡房安置点场地必须考虑的地震问题,并提出了处理地震断层、地表裂缝、砂土液化、坍塌等实际问题的方案;利用强余震的预测结果,分析了这些灾害对场地可能造成的危害;同时对可能潜在的滑坡、危岩崩塌、泥石流等地质灾害提出相应的处理建议,供安置点规划建设参考。     

长春秋季生物质燃烧对PM2.5中WSOC吸光性的影响

为探究长春秋季生物质燃烧对PM_(2.5)中水溶性有机碳(water-soluble organic carbon,WSOC)吸光性的影响,于2017年10～11月进行PM_(2.5)样品采集,对PM_(2.5)中碳质组分、糖类化合物和WSOC的光吸收特征参数进行分析.研究表明:长春秋季PM_(2.5)中WSOC、有机碳(organic carbon,OC)、元素碳(elemental carbon,EC)的平均浓度分别为(10.12±3.47)、(17.07±5.64)和(1.34±0.75)μg·m~(-3),二次有机碳(secondary organic carbon,SOC)对OC的平均贡献率为38.93%.长春秋季总糖浓度为(1 049.39±958.85)ng·m~(-3),其中作为生物质燃烧示踪剂的脱水糖含量(左旋葡聚糖、半乳聚糖和甘露聚糖)在总糖中占比为91.69%,糖类相关性分析结果显示生物质燃烧源为长春秋季大气中糖类物质的主要贡献源.糖类物质的相关性分析及3种脱水糖的特征比值研究显示,作为长春秋季大气主要污染源的生物质燃烧的类型是硬木和作物残渣的燃烧.长春秋季WSOC的光吸收波长指数(AAE)为5.75±1.06,单位质量吸收效率(MAE)为(1.23±0.28)m~2·g~(-1),表明生物质燃烧对WSOC吸光性具有重要影响.利用生物质燃烧特征源参数量化计算生物质燃烧对WSOC浓度的贡献达58.82%,对总WSOC光吸收的贡献达40.92%.     

东南亚生物质燃烧输送影响我国西南气溶胶辐射特性研究

利用2013年地基CE-318太阳光度计观测数据,结合中分辨率成像光谱仪（MODIS）遥感产品和HYSPLIT后向轨迹分析,研究了一次东南亚生物质燃烧污染长距离输送至中国西南昆明站点过程（2013年4月5~8日）中,气溶胶光学特性和辐射特性的变化及其可能来源.结果表明,此次污染过程期间,我国西南地区生物质燃烧活动较少,而中南半岛地区生物质燃烧活动显著.4月5~7日,昆明站点气溶胶光学厚度（AOD）升高,消光波长指数（EAE）和吸收波长指数（AAE）均增大.此外,依据EAE和AAE分类方法,5~6日昆明站点以城市工业气溶胶为主,7~8日以生物质燃烧气溶胶为主,其细模态峰值半径（0.11μm）小于5~6日（0.15μm）,7日细模态粒子体积浓度峰值（约为0.16μm³/μm²）是5日的2倍.气溶胶直接辐射强迫（ARF）日变化结果表明4月7日气溶胶对地表的降温效应达到最大,对大气的加热作用最强.气溶胶直接辐射强迫效率值（ARFE）的变化表明生物质燃烧气溶胶对大气顶的降温作用减弱.MODIS遥感以及HYSPLIT模式后向轨迹表明,此次昆明站点生物质燃烧气溶胶主要来源于东南亚地区（主要是印度北部、印缅北部和不丹地区）.     

长三角背景点夏季大气PM2.5中水溶性无机离子污染特征及来源解析

为研究长三角背景点夏季PM_2.5污染特征,于2018年5月30日—8月15日在上海市崇明岛对PM_2.5样品进行昼夜采集,并对其中水溶性无机离子(Cl-、NO₃-、SO₄2-、Na+、NH₄+、K+、Mg2+、Ca2+)进行了分析.运用PSCF(潜在源贡献)方法判别污染物排放源区,并结合PCA(主成分分析)和PMF(正交矩阵因子)源解析探究PM_2.5来源.结果表明:①观测期间崇明岛ρ(PM_2.5)平均值为(33±21)μg/m3,低于GB 3095—2012《环境空气质量标准》一级标准限值(35 μg/m3),但在部分时段存在显著超标现象,ρ(PM_2.5)最高值在120 μg/m3以上.②水溶性无机离子质量浓度平均值为(14±9.3)μg/m3,占PM_2.5的42.4%,其中SNA(SO₄2-、NO₃-、NH₄+三者统称)为主要离子,占水溶性离子总质量浓度的85.7%.③n(NH₄+)/n(SO₄2-)(NH₄+与SO₄2-的摩尔浓度比)显示,清洁期〔ρ(PM_2.5) < 15 μg/m3〕呈贫铵状态,过渡期〔15≤ρ(PM_2.5)≤35 μg/m3〕和污染期〔ρ(PM_2.5)>35 μg/m3〕均呈富铵状态;过渡期SNA主要以NH₄HSO₄和NH₄NO₃形式存在,而污染期则主要以(NH₄)₂SO₄和NH₄NO₃形式存在.④通过对两次典型污染事件进行离子相关性分析和PSCF分析发现,E1污染事件(5月30日—6月8日)为局地生物质燃烧型污染事件,E2污染事件(7月23日—8月1日)为区域传输污染事件.源解析结果进一步表明,两次典型污染事件期间气态污染物的二次转化对PM_2.5的贡献最显著,贡献率分别为62.8%和59.8%;其次是生物质燃烧,其贡献率分别为32.5%和20.1%;E2污染事件期间海盐源对崇明岛PM_2.5贡献率较高(16.6%),远超过E1污染事件期间对PM_2.5的贡献率(2.7%).研究显示,区域输送对崇明岛PM_2.5有显著贡献,二次颗粒物累积是崇明岛PM_2.5超标的主要原因.      

基于神经网络的东北地区秸秆焚烧预测

选取农作物秸秆露天燃烧严重的东北地区,采用人工神经网络的方法,结合卫星火点和气象数据,开展秸秆露天燃烧预测研究.结果表明：人工神经网络预测模型成功验证了松嫩平原地区2015年10月25日~11月15日的秸秆露天燃烧情况,其准确度为67.1%,经过多次试验,在神经网络建模与验证数据配比为80：20时,预测准确度最高,可达69.7%,同时该模型的稳定性较好.而对不同区域,不同时间段的预测研究表明,人工神经网络较适用于长时间序列的预测.就影响因素而言,相对湿度是影响秸秆露天燃烧的最重要因素.本研究结果可为空气质量模式提供火点预测数据,提高其预报预警能力,为区域联防联控政策的制定提供科技支持.     

基于短时傅里叶变换的干扰信号识别方法

目的提高无线电引信识别欺骗式干扰的能力。方法根据炮弹弹体自旋的特点,使得采用连续波线极化天线的无线电引信所收到的干扰信号呈现出有别于地面回波的周期性幅度调制特征,通过对此特征进行短时傅里叶变换后进行识别,可以作为无线电引信是否受到欺骗式干扰的判断依据。结果通过仿真和试验对方法的可行性进行了验证,表明该识别方法可以很好地提高连续波无线电引信的识别欺骗式干扰的能力。结论基于短时傅里叶变换检测旋转调制的对地旋转弹无线电引信欺骗干扰识别的方法可以对干扰信号特征进行识别,算法处理时间短,能够作为引信是否受到干扰的一种判断依据。