强震作用下超高桥墩动力稳定性理论研究

根据平截面假定,考虑超高桥墩大位移变形产生的几何非线性影响,建立超高桥墩的振动控制微分方程,利用变步长的龙格-库塔法进行求解,结合B-R运动判定准则,对超高桥墩在地震作用下的动力失稳机理进行研究。理论分析表明,超高桥墩的动力失稳与桥墩的几何尺寸、质量分布、边界条件有密切关系;桥墩动力失稳时刻随地震波加速度峰值的增大而减小;失稳时刻与失稳加速度荷载有对应关系。算例结果表明:本文方法正确,利用本文理论能够准确计算超高桥墩的失稳时刻及失稳加速度,对超高桥墩动力失稳的理论分析及工程实践有重要指导意义。     

水力劈裂对岩体中自然裂纹的影响研究

建立了求解自然裂纹和水力裂纹扩展的扩展有限元法,对裂纹附近区域的节点采用广义形函数,并采用线增函数消除混合单元,以提高裂纹附近的精度。引入水力劈裂的非耦合模型,即假设裂纹中的水压力为均布力;用砂浆法（线段-线段接触法）结合增广型拉格朗日乘子法处理受压裂纹段的接触条件。并通过算例分析了以下内容：计算了受压裂纹和裂纹面分布均布水压力的水力裂纹的应力强度因子,并与解析解进行了比较,结果表明,提出的方法具有很高的精度;模拟了水力裂纹对自然裂纹面的影响,并分析了自然裂纹面上的接触力和接触状态。     

地震动力作用下土-地铁隧道模型分析

针对地铁建设中典型的马蹄形断面隧道建立比例尺为1∶20的分析模型,并采用数值分析方法研究马蹄形隧道处于单一土层及工程所处区域典型的成层土体中时的动力响应。分析结果表明,在单一土层中由于土体的约束作用,结构产生的位移以整体沉降为主,在成层土体中除产生一定的整体变形外还伴随一定的扭转变形。在两种地层情况下马蹄形地铁隧道在地震动力作用下的动力加速度响应、竖向位移均在拱顶处产生最大值,其中在单一土层中的加速度响应最大值为结构中部加速度的2.29倍。结构在顶部和侧板处所产生的动应力响应值也较大。研究表明,地震动力荷载作用下顶板、侧板均为受力较大部位,在设计和施工中应予以充分重视。     

基于弹性薄板的不规则采动地表沉陷预计模型

文章借助弹性薄板理论,建立地表沉陷变形的预计模型,并给出任意点地表变形的预计表达式。针对地下开挖空间形状的不规则性,推导出了水平空间、倾斜面空间以及不规则开挖空间：椭圆抛物面空间、二次柱面空间以及二次曲面空间地表沉陷的预计公式。本文的研究结果对该类开采沉陷问题的研究具有一定指导意义。     

GIS and remote sensing integration for environmental applications

Abstract

The combined use of remotely-sensed images and vector GIS data has received considerable interest in recent years. This review article discusses the historical move towards closer integration of remote sensing and GIS technologies and the requirements of integrated software systems to enable remotely-sensed data to be combined with vector datasets for maximum effect. The benefits of integration to users of both GIS and remote sensing for environmental applications are reviewed and some thoughts are given on terminology and future directions in this field.     

An object-based conceptual framework and computational method for representing and analyzing coastal morphological changes

This article presents an object-based conceptual framework and numerical algorithms for representing and analyzing coastal morphological and volumetric changes based on repeat airborne light detection and ranging (LiDAR) surveys. This method identifies and delineates individual zones of erosion and deposition as discrete objects. The explicit object representation of erosion and deposition zones is consistent with the perception and cognition of human analysts and geomorphologists. The extracted objects provide ontological and epistemological foundation to localize, represent, and interpret erosion and deposition patches for better coastal resource management and erosion control. The discrete objects are much better information carriers than the grid cells in the field-based representation of source data. A set of spatial and volumetric attributes are derived to characterize and quantify location, area, shape, orientation, depth, volume, and other properties of erosion and deposition objects. Compared with the conventional cell-by-cell differencing approaches, our object-based method gives a concise and high-level representation of information and knowledge about coastal morphological dynamics. The derived attributes enable the discrimination of true morphological changes from artifacts caused by data noise and processing errors. Furthermore, the concise object representation of erosion and deposition zones facilitates overlay analysis in conjunction with other GIS data layers for understanding the causes and impacts of morphological and volumetric changes. We have implemented a software tool for our object-based morphological analysis, which will be freely available for the public. An example is used to demonstrate the utility and effectiveness of this new method.     

Mode coupling analysis and differential rotation in a flow driven by a precessing cylindrical container

We present a theoretical weakly nonlinear analysis of the dynamics of an inviscid flow submitted to both rotation and precession of an unbounded cylindrical container, by considering the coupling of two Kelvin (inertial) waves. The parametric centrifugal instability known for this system is shown to saturate when one expands the Navier–Stokes equation to higher order in the assumed small precession parameter (ratio of precession to rotation frequencies) with the derivation of two coupled Landau equations suitable to describe the dynamics of the modes. It is shown that an azimuthal mean flow with differential rotation is generated by this modes coupling. The time evolution of the associated dynamical system is studied. These theoretical results can be compared with water experiments and also to some numerical simulations where viscosity and finite length effects cannot be neglected.     

Evaluating legacy contaminants and emerging chemicals in marine environments using adverse outcome pathways and biological effects-directed analysis

Natural and synthetic chemicals are essential to our daily lives, food supplies, health care, industries and safe sanitation. At the same time protecting marine ecosystems and seafood resources from the adverse effects of chemical contaminants remains an important issue. Since the 1970s, monitoring of persistent, bioaccumulative and toxic (PBT) chemicals using analytical chemistry has provided important spatial and temporal trend data in three important contexts; relating to human health protection from seafood contamination, addressing threats to marine top predators and finally providing essential evidence to better protect the biodiversity of commercial and non-commercial marine species. A number of regional conventions have led to controls on certain PBT chemicals over several years (termed ‘legacy contaminants’; e.g. cadmium, lindane, polycyclic aromatic hydrocarbons [PAHs] and polychlorinated biphenyls [PCBs]). Analytical chemistry plays a key role in evaluating to what extent such regulatory steps have been effective in leading to reduced emissions of these legacy contaminants into marine environments. In parallel, the application of biomarkers (e.g. DNA adducts, CYP1A-EROD, vitellogenin) and bioassays integrated with analytical chemistry has strengthened the evidence base to support an ecosystem approach to manage marine pollution problems. In recent years, however, the increased sensitivity of analytical chemistry, toxicity alerts and wider environmental awareness has led to a focus on emerging chemical contaminants (defined as chemicals that have been detected in the environment, but which are currently not included in regulatory monitoring programmes and whose fate and biological impacts are poorly understood). It is also known that natural chemicals (e.g. algal biotoxins) may also pose a threat to marine species and seafood quality. Hence complex mixtures of legacy contaminants, emerging chemicals and natural biotoxins in marine ecosystems represent important scientific, economic and health challenges. In order to meet these challenges and pursue cost-effective scientific approaches that can provide evidence necessary to support policy needs (e.g. the European Marine Strategy Framework Directive), it is widely recognised that there is a need to (i) provide marine exposure assessments for priority contaminants using a range of validated models, passive samplers and biomarkers; (ii) integrate chemical monitoring data with biological effects data across spatial and temporal scales (including quality controls); and (iii) strengthen the evidence base to understand the relationship between exposure to complex chemical mixtures, biological and ecological impacts through integrated approaches and molecular data (e.g. genomics, proteomics and metabolomics). Additionally, we support the widely held view that (iv) that rather than increasing the analytical chemistry monitoring of large number of emerging contaminants, it will be important to target analytical chemistry towards key groups of chemicals of concern using effects-directed analysis. It is also important to evaluate to what extent existing biomarkers and bioassays can address various classes of emerging chemicals using the adverse outcome pathway (AOP) approach now being developed by the Organization for Economic Cooperation and Development (OECD) with respect to human toxicology and ecotoxicology.     

A spectral gradient difference based approach for land cover change detection

Change detection with remotely sensed imagery plays an important role in land cover mapping, process analysis and dynamic information services. Euclidean distance, correlation and other mathematic metrics between spectral curves have been used to calculate change magnitude in most change detection methods. However, many pseudo changes would also be detected because of inter-class spectral variance, which remains a significant challenge for operational remote sensing applications. In general, different land cover types have their own spectral curves characterized by typical spectral values and shapes. These spectral values are widely used for designing change detection algorithms. However, the shape of spectral curves has not yet been fully considered. This paper proposes to use spectral gradient difference (SGD) to quantitatively describe the spectral shapes and the differences in shape between two spectra. Change magnitude calculated in the new spectral gradient space is used to detect the change/no-change areas. Then, a chain model is employed to represent the SGD pattern both qualitatively and quantitatively. Finally, the land cover change types are determined by pattern matching with the knowledgebase of reference SGD patterns. The effectiveness of this SGD-based change detection approach was verified by a simulation experiment and a case study of Landsat data. The results indicated that the SGD-based approach was superior to the traditional methods.     

经验模态分解与神经网络的GPS可降水量预测

本文将经验模态分解与神经网络相结合的方法应用于GPS可降水量预测。对GPS可降水量进行经验模态分解,在分解过程中采用径向基神经网络处理端点问题,针对经验模态分解得到的每个分量分别运用径向基神经网络进行预测,并重构出最后的预测结果。重构结果与直接运用神经网络进行预测的GPS可降水量、实测GPS可降水量进行比较,结果表明,相对于直接预测,经验模态分解与神经网络结合的方法具有更高的预测精度。