大气中粘性效应对三维地形波及其波动阻力的影响

采用两层大气模式, 通过引入瑞利摩擦系数来定性描述大气中粘性机制, 讨论了粘性效应对三维简单地形波及其波动阻力的影响。结果表明,无论低层大气为稳定层结还是不稳定层结, 大气中粘性的存在将减弱地形波的强度, 减小其产生的波动阻力     

Bivariate Gaussian mixture–based equivalent linearization method for stochastic seismic analysis of nonlinear structures

To address challenges in stochastic seismic analysis of nonlinear structures, this paper further develops a recently proposed Gaussian mixture–based equivalent linearization method (GM‐ELM). The GM‐ELM uses a Gaussian mixture distribution model to approximate the probabilistic distribution of a nonlinear system response. Using properties of the Gaussian mixture model, GM‐ELM can decompose the non‐Gaussian response of a nonlinear system into multiple Gaussian responses of linear single–degree of freedom oscillators. With the set of the equivalent linear systems identified by GM‐ELM, response statistics as crossing rate and first‐passage probability can be computed conveniently using theories of linear random vibration analysis. However, the original version of GM‐ELM may lead to an inaccurate estimate because of the heuristic parameters of the linear system introduced to supplement insufficient information. To overcome this limitation and define unique equivalent linear systems, this paper proposes a further developed version of GM‐ELM, which uses a mixture of bivariate Gaussian densities instead of univariate models. Moreover, to facilitate the use of elastic response spectra for estimating the mean peak responses of a nonlinear structure, a new response spectrum combination rule is proposed for GM‐ELM. Two numerical examples of hysteretic structural systems are presented in this paper to illustrate the application of the bivariate GM‐ELM to nonlinear stochastic seismic analysis. The analysis results obtained by the bivariate GM‐ELM are compared with those obtained by the univariate GM‐ELM, the conventional equivalent linearization method, the tail equivalent linearization method, and Monte Carlo simulation. The supporting source code and data are available for download at https://github.com/yisangri/GitHub‐bGM‐ELM‐code.git     

鄂尔多斯地块—扬子地块深部电性结构特征及其动力学意义

位于青藏高原东北缘的秦岭造山带在大地构造上南接扬子地块、北接华北地块,是特提斯构造域和古亚洲洋构造域的转换带。本文基于对一条起始于扬子地块,穿过秦岭造山带和鄂尔多斯地块,到达河套地堑的南北向大地电磁测深剖面的研究,探讨秦岭造山带和其北侧的鄂尔多斯地块、南侧的扬子地块之间的接触关系,以及青藏高原物质东北向逃逸等地学问题。对实测数据进行了张量阻抗分解和维性分析等工作,并对剖面进行了二维反演,获得岩石圈电性结构模型。根据电阻率模型认为:在秦岭造山带北部发现大规模"瓶颈状"分布的低阻异常体(C2),可能为华北、华南地块双向俯冲前缘地幔物质的上涌通道,或者是青藏高原中、下地壳物质沿秦岭造山带中构造薄弱位置向东逃逸的通道;在秦岭造山带和大巴山弧形带边界处发现南倾的低阻异常(C1),解释为大巴山弧形带北缘的逆冲断裂在电性上的反映;电性结构模型中,扬子地块高阻异常体(R2、R3和R4)向北倾斜至秦岭造山带下方,而北部鄂尔多斯地块的高阻异常体(R5和R6)向南倾斜至秦岭造山带下方;高阻异常通常被认为是稳定岩石圈的反映,据此推断这两组相向俯冲至秦岭造山带下方的高阻异常是华北地块和扬子地块向秦岭造山带下方汇聚的电性结构探测依据;鄂尔多斯地块南、北电性差异较大,北部中、下地壳大规模分布电阻率值在3～100Ω·m之间的低阻异常体,可能为地幔上涌导致的局部熔融或含盐流体共同作用的结果。     

基于组合权重与灰色关联度分析法的地铁深基坑开挖稳定性评价

伴随着城市的快速发展,地铁深基坑工程越来越多。在开挖过程中如何对其稳定性进行评价,是当前需要重点关注的问题。以成都地铁十七号线凤溪站深基坑支护开挖工程为依托,利用层次分析确定的主观权重与利用熵值法确定的客观权重计算获得组合权重,并与灰色关联度分析法相结合,通过现场数据采集并进行综合评判,客观评价地铁深基坑开挖的稳定性。结果表明,各监测项目对基坑稳定性的重要程度从大到小依次为桩顶水平位移（0.29）、地表沉降（0.24）、建筑物沉降（0.19）、桩顶沉降（0.18）、内支撑轴力（0.10）,基坑稳定性综合评判结果等级为"非常好"。所建立的评价模型可为类似地铁深基坑开挖稳定性评价提供新的方法。     

Measurement of local and volumetric deformation in geotechnical triaxial testing using 3D-digital image correlation and a subpixel edge detection algorithm

Based on the three-dimensional digital image correlation (3D-DIC) technique, the stereovision system has been applied to the improved triaxial apparatus to obtain 3D full-field deformation of the specimen during triaxial testing. Through the calibration process, the 3D-DIC technique can obtain the accurate specimen’s spatial displacement deformation. Meanwhile, a subpixel edge detection algorithm has been combined with 3D-DIC technique to calculate the radial strain and the volume strain of the specimen directly. Furthermore, a series of consolidated drained and undrained triaxial tests were carried out on Hainan (China) sand specimens and measured by the conventional and the image measurement methods. Compared to the results measured by the conventional method, the image measurement technique can obtain the more experimental data, such as the 3D displacement field of the whole specimen, the local strain distribution, and so on. The measurement results also show the conventional method would be disturbed by the end constraints in triaxial tests so that the strength of the soil would be overestimated. Meanwhile, the middle of the specimen would be selected to calculate the stress–strain relationship without the influence of the end constraints in the proposed method. Based on the image measurement results, the proposed method has the potential to be used in geotechnical tests for exploring the soil’s progressive failure behaviors, inhomogeneous deformation and mechanical characteristics.

     

上海和北京城市创新空间结构的时空演化模式

基于城市邮编区划空间数据库,从创新产出的视角建构城市创新评价指标体系,对1991-2014年上海市和北京市的创新空间结构的空间演化模式进行了探讨。研究发现：① 邮政区划为研究城市创新空间结构的生长提供了全新的视角,基于随机边缘点连线以及泰森多边形法构建的城市邮编空间数据库评价城市创新空间结构的结果较为理想,因此具有推广价值;② 25年间,上海市和北京市的创新空间结构生长体现出了诸多的共性特征：随着参与创新的城市空间单元逐年增加,区域创新产出虽总体差距在缩小,但空间集聚趋势在加剧;③ 25年间,上海市和北京市的创新空间结构生长也体现出了共性上的差异性,其中上海市创新空间结构在创新资源郊区化转移的趋势下,呈现出由单核驱动向多核共振演进,以交通干道为空间扩散廊道的辐射效应凸显,相应的,其创新产出空间关联效应也显现出了市中心空心化现象;而北京市创新空间结构始终为市中心单核主导型,并在创新资源不断向中心集聚趋势下,其创新产出空间关联效应呈现出“农村包围城市”的演化特征;④ 上海市和北京市创新空间结构与其所在的区域创新空间结构（长三角城市群和京津冀城市群）具有内在的一致性,表明城内尺度科技创新活动空间分布的均衡与非均衡规律与其所处的区域创新格局密切相关。     

Phylogenetic diversity of planktonic bacteria in the Chukchi Borderland region in summer

Planktonic bacteria are abundant in the Chukchi Borderland region. However, little is known about their diversity and the roles of various bacteria in the ocean. Seawater samples were collected from two stations K2S and K4S where sea ice was melting obviously. The analysis of water samples with fluorescence in situ hybridization (FISH) showed that DMSP-degrading bacteria accounted for 13% of the total bacteria at the station K2S. No aerobic anoxygenic phototrophic (AAP) bacteria were detected in both samples. The bacterial communities were characterized by two 16S rRNA gene clone libraries. Sequences fell into four major lineages of the domain Bacteria, including Proteobacteria (Alpha, Beta and Gamma subclasses), Bacteroidetes, Actinobacteria and Firmicutes. No significant difference was found between the two clone libraries. SAR11 and Rhodobacteraceae clades of Alphaproteobacteria and Pseudoalteromonas of Gammapro-teobacteria constituted three dominant fractions in the clone libraries. A total of 191 heterotrophic bacterial strains were isolated and 76% showed extracellular proteolytic activity. Phylogenetic analysis reveals that the isolates fell into Gammaproteobacteria, Bacteroidetes, Actinobacteria and Firmicutes. The most common genus in both the bacterial isolates and protease-producing bacteria was Pseudoalteromonas. UniFrac data showed suggestive differences in bacterial communities between the Chukchi Borderland and the northern Bering Sea.     

Nitrogen budget of the eelgrass, Zostera marina in a bay system on the south coast of Korea

Above- and below-ground productivities and tissue N content were measured monthly to quantify N incorporation to sustain eelgrass growth in Koje Bay on the south coast of Korea from January to December 2002. N acquisition was also estimated through measurements of N uptake kinetics, tissue biomass, and in situ inorganic N concentrations in water column and sediments. Above- and below-ground productivities were highest in summer and lowest in late fall and winter. Leaf tissue N content was highest in December and lowest in July, while rhizome tissue N content was highest in October and lowest in April. Estimated monthly N incorporation by leaf tissues based on the leaf productivity and N content ranged from 0.4 g N m^?2 month^?1 in November to 2.0 g N m^?2 month^?1 in May. N incorporation by below-ground tissues ranged from 0.1 g N m^?2 month^?1 in February to 0.2 g N m^?2 month^?1 in October. Annual whole plant N incorporation was 14.5 g N m^?2 y^?1, and N incorporation by leaf tissues accounted for about 87 % of total N incorporation. Maximum uptake rate (V _max ) and half saturation constant (K _m ) of leaf NH₄ ⁺ uptake were significantly lower than those of root NH₄ ⁺ uptake. Above- and below-ground biomass ranged from 20.8 g DW m^?2 and 8.6 g DW m^?2 in winter to 350.0 g DW m^?2 and 81.3 g DW m^?2 in spring, respectively. NH₄ ⁺ concentrations varied from 0.2 to 4.3 mM in water column and from 93.0 to 551.7 mM in sediment pore water. Based on these measurements, annual N acquisition by root tissues contributed slightly higher than that by leaf tissues to total plant N acquisition. During winter, monthly leaf N acquisition was lower than monthly leaf N incorporation. This implies that Z. marina has internal nitrogen retention system to offset the shortage and excess of nitrogen.     

Estimation of non-CO2 GHGs emissions by analyzing burn severity in the Samcheok fire, South Korea

This study was performed to estimate the emission of non-CO 2 greenhouse gases(GHGs) from biomass burning at a large fire area.The extended methodology adopted the IPCC Guidelines(2003) equation for use on data from the Samcheok forest fire gathered using 30 m resolution Landsat TM satellite imagery,digital forest type maps,and growing stock information per hectare by forest type in 1999.Normalized burn ratio(NBR) technique was employed to analyze the area and severity of the Samcheok forest fire that occurred in 2000.The differences between NBR from pre-and post-fire datasets are examined to determine the extent and degree of change detected from burning.The results of burn severity analysis by dNBR of the Samcheok forest fire area revealed that a total of 16,200 ha of forest were burned.The proportion of the area characterized by a ’Low’ burn severity(dNBR below 152) was 35%,with ’Moderate’(dNBR 153-190) and ’High’(dNBR 191-255) areas were at 33% and 32%,respectively.The combustion efficiency for burn severity was calculated as 0.43 for crown fire where burn severity was ’High’,as 0.40 for ’Moderate’ severity,and 0.15 for ’Low’ severity surface fire.The emission factors for estimating non-CO 2 GHGs were separately applied to CO 130,CH 4 9,NO x 0.7 and N 2 O 0.11.Non-CO 2 GHGs emissions from biomass burning in the Samcheok forest fire area were estimated to be CO 44.100,CH 4 3.053,NO x 0.238 and N 2 O 0.038 Gg.