Analytical solutions of the diffraction problem of a group of truncated vertical cylinders

An exact analytical method is described to solve the diffraction problem of a group of truncated vertical cylinders. In order to account for the interaction between the cylinders, Kagemoto and Yue's exact algebraic method is utilised. The isolated cylinder diffraction potential due to incident waves is obtained using Garret's solution and evanescent mode solutions are derived in a similar manner.Numerical results are presented for arrays of two and four cylinders. Comparisons between the results obtained from the method presented here and those obtained from numerical methods show excellent agreement.     

小型氰化厂的技术管理

本文简述了小型氰化厂的技术管理方法和实际操作过程,应用该方法提高选矿厂的生产技术指标和经济效益。     

Improving neural network performance on the classification of complex geographic datasets

Neural Networks are now established computational tools used for search minimisation and data classification. They offer some highly desirable features for landuse classification problems since they are able to take in a variety of data types, recorded on different statistical scales, and combine them. As such, neural networks should offer advantages of increased accuracy. However, a barrier to their general acceptance and use by all but `experts' is the difficulty of configuring the network initially.  This paper describes the architectural problems of applying neural networks to landcover classification exercises in geography and details some of the latest developments from an ongoing research project aimed at overcoming these problems. A comprehensive strategy for the configuration of neural networks is presented, whereby the network is automatically constructed by a process involving initial analysis of the training data. By careful study of the functioning of each part of the network it is possible to select the architecture and initial weights on the node connections so the constructed network is `right first time'. Further adaptations are described to control network behaviour, to optimise functioning from the perspective of landcover classification. The entire configuration process is encapsulated by a single application which may be treated by the user as a `black box', allowing the network to the applied in much the same way as a maximum likelihood classifier, with no further effort being required of the user.     

Northern North American Tree-Ring Evidence for Regional Temperature Changes after Major Volcanic Events

Maximum latewood density data from trees at thirteen temperature-sensitive sites along the northern treeline of North America are used to evaluate the spatial patterns of response to four known volcanic events just prior to the period of modern observations: in 1640, 1783, 1815 and 1835. A previously unknown event is also postulated for 1699. This tree-ring density parameter is used because it shows a stronger and more consistent short-term, temperature-related volcanic signal than ring width. Normalized density departures following these events vary in sign and magnitude from region to region, with the coldest summer conditions inferred for the Northwest Territories in 1641, Alaska in 1783, Quebec and Labrador in 1816 and the Northwest Territories in 1836. For these as well as other events, low density values are often among the most extreme on record at their respective locations. We suggest that these regional variations in tree growth reflect cooling induced by volcanism and the distribution of cooling influenced by atmospheric circulation patterns.     

甘肃迭部M_s4.0地震震源机制解和震源深度精确测定

综合利用了2011年2月23日迭部M_s4.0地震的近震宽频带波形资料,采用CAP方法反演了该地震的震源机制解和震源深度,结合深度震相sPL对震源深度进行了精确确定。结果表明:迭部4.0级地震是一次走滑兼逆冲型地震;最佳双力偶解为节面Ⅰ走向110°、倾角57°,滑动角23°;发震构造可能为光盖山-迭山北麓断裂;震源深度为7 km。     

Conditional heavy-tail behavior with applications to precipitation and river flow extremes

This article deals with the right-tail behavior of a response distribution \(F_Y\) conditional on a regressor vector \({\mathbf {X}}={\mathbf {x}}\) restricted to the heavy-tailed case of Pareto-type conditional distributions \(F_Y(y|\ {\mathbf {x}})=P(Y\le y|\ {\mathbf {X}}={\mathbf {x}})\), with heaviness of the right tail characterized by the conditional extreme value index \(\gamma ({\mathbf {x}})>0\). We particularly focus on testing the hypothesis \({\mathscr {H}}_{0,tail}:\ \gamma ({\mathbf {x}})=\gamma _0\) of constant tail behavior for some \(\gamma _0>0\) and all possible \({\mathbf {x}}\). When considering \({\mathbf {x}}\) as a time index, the term trend analysis is commonly used. In the recent past several such trend analyses in extreme value data have been published, mostly focusing on time-varying modeling of location or scale parameters of the response distribution. In many such environmental studies a simple test against trend based on Kendall’s tau statistic is applied. This test is powerful when the center of the conditional distribution \(F_Y(y|{\mathbf {x}})\) changes monotonically in \({\mathbf {x}}\), for instance, in a simple location model \(\mu ({\mathbf {x}})=\mu _0+x\cdot \mu _1\), \({\mathbf {x}}=(1,x)'\), but the test is rather insensitive against monotonic tail behavior, say, \(\gamma ({\mathbf {x}})=\eta _0+x\cdot \eta _1\). This has to be considered, since for many environmental applications the main interest is on the tail rather than the center of a distribution. Our work is motivated by this problem and it is our goal to demonstrate the opportunities and the limits of detecting and estimating non-constant conditional heavy-tail behavior with regard to applications from hydrology. We present and compare four different procedures by simulations and illustrate our findings on real data from hydrology: weekly maxima of hourly precipitation from France and monthly maximal river flows from Germany.     

Research on progressive failure process of Baishuihe landslide based on Monte Carlo model

To the progressive landslide, development of the internal deformation and failure situation can’t be accurately reflected by the overall stability of coefficients and failure probability. But this problem can be solved by utilizing the principle of progressive failure by slices. Taking the warning area of Baishuihe landslide as an example, 5 days accumulated rainfall in different reappearing period is computed by Gumbel model. The failure probability of each slice is calculated by progressive failure principle, which is based on Monte Carlo model. The following results can be revealed through calculation: Overall stability and failure probability can’t reflect real situation of Baishuihe landslide warning area. Through building the calculation of progressive failure model of each slice, the stability of each part in the Baishuihe landslide warning area is quite different. Unstable region mainly lies in vicinity of the middle and posterior warning area. The front of the warning area remains stable. Deformation characteristics of the warning area are consistent with the investigation report. The scope of unstable area increased gradually with rainfall and the decline of reservoir water. Under 5 day’s accumulated rainfall of 50 years, the poor stable and unstable region reached 75 %, there is a large possibility of local deformation slip. Under the joint action of rainfall and reservoir water level, the warning area of Baishuihe landslide shows a progressive failure mode from top to bottom.     

Spectral simulation of vector random fields with stationary Gaussian increments in <Emphasis Type="Italic">d</Emphasis>-dimensional Euclidean spaces

This paper addresses the problem of simulating multivariate random fields with stationary Gaussian increments in a d-dimensional Euclidean space. To this end, one considers a spectral turning-bands algorithm, in which the simulated field is a mixture of basic random fields made of weighted cosine waves associated with random frequencies and random phases. The weights depend on the spectral density of the direct and cross variogram matrices of the desired random field for the specified frequencies. The algorithm is applied to synthetic examples corresponding to different spatial correlation models. The properties of these models and of the algorithm are discussed, highlighting its computational efficiency, accuracy and versatility.     

Identification and assessment of water safety risk for groundwater recharge with reclaimed water in China

Groundwater recharge using reclaimed water has developed rapidly around the world to relieve the groundwater resource shortage and declining of the water table. Traditional water treatment systems are inefficient to remove all the types of contaminants, so it is urgent to identify the priority chemical substances (CSs) that deserve our first concern. In this study, we developed a method (EER method) to identify priority CSs in groundwater recharge by surface spreading and direct aquifer injection. Three stages were processed which were exposure assessment, effect assessment and ranking for identification of priority CSs. Fourteen cities in China were selected for data collected and 90 pollutants in reclaimed water samples were analyzed as the target pollutants for a case study. According to three stages, the 90 CSs studied were divided into five groups (primary control CSs and high, moderate and low and no risk control CSs). In the primary control CSs and high, moderate and low and no risk control CSs group there were 14, 18, 21, 21 and 16 CSs, respectively when groundwater recharged by surface spreading, while there were 15, 18, 21, 21 and 15 CSs when recharged by direct injection. This method provided an indicator of prioritizing the risk of 90 compounds in the reclaimed water for groundwater recharge.