Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

Pervasive wetland flooding in the glacial drift prairie of North Dakota (USA)

This article describes a unique flood hazard, produced by the dramatic expansion of wetlands in Nelson County, located within the North American Prairie Pothole Region of North Dakota, USA. There has been an unprecedented increase in the number, average size, and permanence of prairie wetlands, and a significant increase in the size of a closed lake (Stump Lake) due to a decade-long wet spell that began in 1993 following a prolonged drying trend. Base-line land cover information from the 1992 USGS National Land Cover Characterization dataset, and a Landsat TM scene acquired 9 July 2001 are used to assess the growth of the closed lake and wetland pond surface areas, and to analyze the type and area of various land cover classes inundated between 1992 and 2001. The open water profile in Nelson County changed from one marked by relatively comparable coverage of closed lake and wetland pond areas in 1992, to one in which wetland open water accounted for the vast majority of total open water in 2001. The bulk of the wetland pond area expansion occurred by displacing existing wetland vegetation and agricultural cropland. Producers responded to the flood hazard by filing Federal Crop Insurance Corporation (FCIC) claims and enrolling cropland in the Conservation Reserve Program (CRP), a federal land retirement program. Land taken out of agricultural production has had an enormous impact upon the agricultural sector that forms the economic base of the rural economy. In 2001 the land taken out of production due to CRP enrollment and preventive planting claims represented nearly 42% of Nelson County’s 205.2 K ha base agricultural land. The patterns obtained from this detailed study of Nelson County are likely to be the representative of the more publicized flood disaster occurring within the Devils Lake Basin of North Dakota.     

Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey)

In the international literature, although considerable amount of publications on the landslide susceptibility mapping exist, geomorphology as a conditioning factor is still used in limited number of studies. Considering this factor, the purpose of this article paper is to implement the geomorphologic parameters derived by reconstructed topography in landslide susceptibility mapping. According to the method employed in this study, terrain is generalized by the contours passed through the convex slopes of the valleys that were formed by fluvial erosion. Therefore, slope conditions before landsliding can be obtained. The reconstructed morphometric and geomorphologic units are taken into account as a conditioning parameter when assessing landslide susceptibility. Two different data, one of which is obtained from the reconstructed DEM, have been employed to produce two landslide susceptibility maps. The binary logistic regression is used to develop landslide susceptibility maps for the Melen Gorge in the Northwestern part of Turkey. Due to the high correct classification percentages and spatial effectiveness of the maps, the landslide susceptibility map comprised the reconstructed morphometric parameters exhibits a better performance than the other. Five different datasets are selected randomly to apply proper sampling strategy for training. As a consequence of the analyses, the most proper outcomes are obtained from the dataset of the reconstructed topographical parameters and geomorphologic units, and lithological variables that are implemented together. Correct classification percentage and root mean square error (RMSE) values of the validation dataset are calculated as 86.28% and 0.35, respectively. Prediction capacity of the different datasets reveal that the landslide susceptibility map obtained from the reconstructed parameters has a higher prediction capacity than the other. Moreover, the landslide susceptibility map obtained from the reconstructed parameters produces logical results.     

陕西白河县月儿潭绿松石与次生磷钙铝矾研究

对陕西省白河县月儿潭风化严重的绿松石样品进行了岩石薄片观察、化学成分测试、X射线粉晶衍射和红外吸收光谱分析等研究.结果表明,绿松石风化分解由天蓝色退色成黄绿色,最后变成白色,结构也由致密细腻变得松散多孔,主要原因是发生了硫酸根对磷酸根的交代作用,最终的交代产物主要是磷钙铝矾.     

GPS变形监测平差计算及不确定度分析

全球定位系统（GPS）是一种全天候、高精度的连续定位系统,它以速度快、方法灵活多样、操作简便等优势被广泛应用于工程测量和变形监测中。结合水厂铁矿GPS边坡变形监测实例,对GPS监测网的星历预报、基线向量平差计算、网平差计算、结果及残差不确定度进行了细致分析研究,以验证GPS技术在边坡变形监测中的可靠性和精度。     

Re-Os同位素对峨眉山大火成岩省成因制约的探讨

峨眉山大火成岩省（ELIP）主要由玄武岩、玄武质火山碎屑岩及少量的苦橄岩（包括越南的科马提岩）、长英质岩石以及层状岩体和岩墙组成,其物质来源直接关系到其成因是否与地幔柱活动有关。Re-Os同位素体系是地核、地幔和地壳物质的最佳示踪剂。前人对ELIP内的Re-Os同位素研究表明,低Ti玄武岩的Os含量为0．006×10^-9-0．40010^-9,^187Os／^188Os初始值为0．1371～1．403,并提出其与地幔柱活动有关;而高Ti玄武岩的Os含量为0．00410^-9～0．56010^-9,^187Os／^188Os初始值为0．1271～5．19,认为起源于大陆岩石圈地幔或地幔柱上升过程中受到大量岩石圈地幔“混染”（xu JF et al．,2007）;科马提岩的0s含量为1．2410^-9～7．0010^-9,^187Os／^188Os初始值为0．1251～0．1261,苦橄岩的Os含量为0．3210^-9～2．32910^-9,^187Os／^188Os初始值为0．1233～0．1266,指示苦橄岩和科马提岩均来自亏损地幔源区（Hanski et al．,2004;陈雷等,2007）。本文利用Os含量最低、^187Os／^188Os最高的高Ti玄武岩作为地壳端员,用铁质陨石、原始上地幔（PUM）和亏损地幔（DMM）作为地核和各种地幔端员,分别做二元混合计算,结果显示绝大多数玄武岩和所有苦橄岩及科马提岩均落在地壳和DMM混合曲线附近,并且邻区特提斯洋地幔岩与DMM具有相近的Os含量和^187Os／^188Os组成,据此推测峨眉山火成岩的形成与特提斯洋的活动有关,主要受控于地壳和亏损地幔的相互作用。     

Reduction of hydroelastic responses of a very-long floating structure by a floating oscillating-water-column breakwater system

The hydroelastic responses of a very-long floating structure (VLFS) placed behind a reverse T-shape freely floating breakwater with a built-in oscillating water column (OWC) chamber are analyzed in two dimensions. The Bernoulli–Euler beam equation is coupled with the equations of rigid and elastic motions of the breakwater and the VLFS. The interaction of waves between the floating rigid breakwater and the elastic VLFS is formulated in a consistent manner. It has been shown numerically that the structural deflections of the VLFS can be reduced significantly by a suitably designed reverse T-shape floating breakwater.     

Numerical study of the motions and drift force of a floating OWC device

The motion and the drift force of a floating OWC (oscillating water column) wave energy device in regular waves are studied taking account of the oscillating surface-pressure due to the pressure drop across the duct of the air chamber. The potential problem inside the chamber is formulated by making use of the Green integral equation associated with the Rankine-type Green function while the outer problem with the Kelvin-type Green function. The added mass, wave damping and excitation coefficients as well as the motion and drift force of the OWC device are calculated for various values of parameter related to the pressure drop.     

165°E赤道太平洋溶解氧垂直分布异常分析

根据1986—1990中美热带西太平洋海气相互作用8个航次合作综合调查资料，分析了1987年10月赤道中西太平洋165°E（10°N－6°S）次表层水形成溶解氧最大值的原因。1986－1987年E1Nino衰退时期，该海域赤道附近在E1Nino强盛时期下沉的次表层水开始回升，短时期内形成了类似于中、高纬度海域的理化环境，使浮游生物在混合层内聚集生长，最终导致溶解氧含量在次表层出现最大值和过饱和含量。     

Prediction of local scour around circular piles under waves using a novel artificial intelligence approach

Abstract

The scour phenomena around vertical piles in oceans and under waves may influence the structure stability. Therefore, accurately predicting the scour depth is an important task in the design of piles. Empirical approaches often do not provide the required accuracy compared with data mining methods for modeling such complex processes. The main objective of this study is to develop three data-driven methods, locally weighted linear regression (LWLR), support vector machine (SVR), and multivariate linear regression (MLR) to predict the scour depth around vertical piles due to waves in a sand bed. It is the first effort to develop the LWLR to predict scour depth around vertical piles. The models simulate the scour depth mainly based on Shields parameter, pile Reynolds number, grain Reynolds number, Keulegan–Carpenter number, and sediment number. 111 laboratory datasets, derived from several experimental studies, were used for the modeling. The results indicated that the LWLR provided highly accurate predictions of the scour depths around piles (R?=?0.939 and RMSE = 0.075). Overall, this study demonstrated that the LWLR can be used as a valuable tool to predict the wave-induced scour around piles.