某水电站某泥石流沟综合治理概述

某水电站某泥石流沟内常年流水,属季节性排洪沟谷,水动力类型为暴雨,沟内松散物源丰富,具有泥石流发生条件。在上游区以拦挡泥石流为主,通过修建拦挡措施,减少形成泥石流的固体物质,在下游区以防水、边坡防护及引流等措施,通过修建溢流坝截断上游水流对沟内堆渣体渗流影响;通过修建排洪渠及排洪洞引流;通过削坡、修坡进行边坡维护加固。确保了导流洞出口及上下行交通洞进出口的施工期安全及运行安全。     

Seesaw Pattern of Rainfall Anomalies between the Tropical Western North Pacific and Central Southern China during Late Summer

It is well known that suppressed convection in the tropical western North Pacific(WNP) induces an anticyclonic anomaly,and this anticyclonic anomaly results in more rainfall along the East Asian rain band through more water vapor transport during summer, as well as early and middle summer. However, the present results indicate that during late summer(from mid-August to the beginning of September), the anomalous anticyclone leads to more rainfall over central southern China(CSC), a region quite different from preceding periods. The uniqueness of late summer is found to be related to the dramatic change in climatological monsoon flows: southerlies over southern China during early and middle summer but easterlies during late summer. Therefore, the anomalous anticyclone, which shows a southerly anomaly over southern China, enhances monsoonal southerlies and induces more rainfall along the rain band during early and middle summer. During late summer,however, the anomalous anticyclone reflects a complicated change in monsoon flows: it changes the path, rather than the intensity, of monsoon flows. Specifically, during late summers of suppressed convection in the tropical WNP, southerlies dominate from the South China Sea to southern China, and during late summers of enhanced convection, northeasterlies dominate from the East China Sea to southern China, causing more and less rainfall in CSC, respectively.     

鲜水河下游泥石流发育分布特征研究

鲜水河下游流域处于鲜水河断裂带之南西,总体呈南北走向.受地层岩性、地质构造、新构造活动、河谷地貌演化及气候条件等的控制,流域内泥石流较发育,属泥石流中等发育区.泥石流以暴雨沟谷型泥石流为主,可见少量暴雨坡面型泥石流及古冰川泥石流.泥石流多集中发育于岩性相对软弱的板岩、千枚岩及砂岩与板岩互层的相对宽谷段,多为粘性泥石流.泥石流一般具有多期次发育特征,且规模逐次减小.流域内绝大部分泥石流处于停歇或衰退状态,现代活动性不活跃,现代活动泥石流频度低、规模小,且多发育于植被破坏较严重区域.流域内泥石流活动具有退化的特征,对当地人民生命安全及两河口水库的淤积等影响不大.     

Late glacial fans in the eastern Skagerrak; depositional environment interpreted from swath bathymetry and seismostratigraphy

The origin of acoustically transparent fan deposits overlying glacial till and ice-proximal sediments on the southern margin of the Norwegian Channel has been studied using high-resolution seismic-reflection profiles and multibeam bathymetry. The first deposits overlying glacigenic sediments are a series of stacked, acoustically transparent submarine fans. The lack of glaciomarine sediments below and between individual fans indicates that deposition was rapid and immediately followed the break up of the Late Weichselian ice cover. The fans are overlain by stratified glaciomarine sediments and Holocene mud. Because of the uniformity of this drape, the upper surface of the fan deposits is mimicked at the present seafloor, and the bathymetric images clearly show the spatial relationship of the fans to bedrock ridges and the presence of braided channel-levee systems on the surface of the youngest fans. The acoustically transparent character of the fan deposits indicates that they comprise silt and clay, and their lobate form and lack of internal stratification indicates that they were deposited by debris flows. The channel-levee morphology indicates deposition from more watery hyperconcentrated fluid flows. The fan sediments were either derived from 1) erosion of Mid Weichselian lake deposits in southern Skagerrak or 2) from Late glacial ice-margin lake deposits, ponded against the Norwegian Channel ice stream, which collapsed catastrophically when the lateral support was removed as the ice disintegrated. Fans composed almost exclusively of fine-grained sediment need not, therefore, rule out an origin in a deglacial setting relatively close to the former margins of glaciers and ice sheets.     

复杂工程系统优化设计初探--以某泥石流防治工程系统的优化设计为例

以某泥石流防治工程系统的优化设计为例 ,建立了优化模型 ,分析确定了模型参数 ,并利用基于随机模拟的遗传算法对模型进行了求解。对其他泥石流防治工程系统的优化设计具有重要指导意义 ,对复杂工程系统的优化设计也具有普遍的参考价值     

基于兰利法的泥石流临界雨量实验研究

分析了目前泥石流临界雨量确定常用方法存在的问题 ,以及泥石流临界雨量实验研究中实验降雨量确定的随意性和盲目性 ,提出以兰利 ( Langlie)法为指导进行实验 ,使实验降雨量的确定有了理论依据 ,减少了取得可靠实验结果所需实验次数 ,从而使泥石流临界雨量实验研究更趋完善和可行     

中国城市网络关联格局的影响因素分析——基于电子信息企业网络的视角

城市网络关联格局影响因素的测度及其作用机理的解析是建立城市网络理论模型的关键环节。基于2017年中国电子信息100强企业网络视角构建城市网络,采用指数随机图模型定量测度了中国城市网络的影响因素,解析了城市网络生长发育的微观过程,并探索性的提出了理解中国城市网络发育机理的概念框架。研究发现：偏好依附效应和接收者（GDP）效应构成了中国城市网络中心性格局的微观基础,中国城市网络生长发育表现为择优选择的地理过程;互惠性链接深刻影响着城市间的关系格局,网络闭合机制逐步成为城市间链接关系的重要影响因素;空间距离对基于电子信息企业网络的城市网络约束作用并不明显,城市网络表现出在“流动空间”中生长发育的特征。     

检测前跟踪框架下利用蒙特卡洛算法的空间碎片跟踪策略研究（英文）

在轨卫星或者空间碎片数量的增多,是对空间目标地基自动观测的一个挑战。尽管北美防空司令部编目管理了绝大多数直径超过10 cm的空间物体,但由于轨道摄动,空间目标的位置信息(基于6个轨道根数)依然非常重要,并需要定期更新。在过去的几十年里,配备电子传感器的现代地基光电望远镜已广泛用于天体测量领域。然而,这种设备的跟踪性能主要取决于空间目标的大小和亮度。这些目标所在的天文图像会有不同的背景;而且,在基于凝视模式的短曝光实时观测过程中,运动目标和背景恒星在不同的信噪比下显示为类似的点扩散函数,难以辨认。本研究是为了实现对非高斯和动态背景的高灵敏度检测和跟踪能力的提高,并具有简单的系统机制和出色的计算效率。为突破该限制,将重点放在利用状态估计技术对微小卫星和暗弱目标进行跟踪上。提出一种基于神经网络的自适应运行高斯平均算法,用以从恒星背景及干扰下提取运动的空间目标。该方法随后被集成到了一个检测前跟踪框架中。该框架利用基于蒙特卡洛的粒子滤波跟踪空间目标。三段来自亚太地基光学空间目标观测系统(APOSOS)图像序列被用来对该跟踪策略进行评估。实验结果表明,该方法能够达到满意的跟踪性能。     

南水北调西线工程泥石流灾害及危险区划

南水北调西线工程是拟议中的国家重大建设工程,通过"五坝七洞一渠"共计260km的引水线路,引长江上游雅砻江和大渡河水入黄河。泥石流在工程区多有分布,现已查明,工程区共有不同危险度等级的泥石流沟103条。泥石流危险区划结果表明,研究区内没有泥石流极高危险区;泥石流高度危险区总面积为73km2,主要集中分布在杜柯河流域,达曲和泥曲流域有零星分布;泥石流中度危险区总面积114·75km2,各流域均有分布,其中杜柯河和达曲流域分布较多;泥石流低度危险区是分布最广的区域,总面积156·75km2,各流域均有分布,以杜柯河流域分布略多。研究表明,用单沟泥石流危险度值作为综合指标,以具有不同泥石流危险度等级的泥石流沟流域面积作为权重的加权平均方法,采用网格作为泥石流危险区划的基本单元,能够直接而真实地获得泥石流危险区划的成果。用本文提出的方法进行地质灾害的危险区划,无疑比用间接方法和替代指标得出的危险区划结果具有更高的可靠性。     

The Basic Shape Classification of Space Debris with Light Curves

We study the machine learning method for classifying the basic shape of space debris in both simulated and observed data experiments, where light curves are used as the input features. In the dataset for training and testing, simulated light curves are derived from four types of debris within different shapes and materials. Observed light curves are extracted from Mini-Mega TORTORA (MMT) database which is a publicly accessible source of space object photometric records. The experiments employ the deep convolutional neural network, make comparisons with other machine learning algorithms, and the results show CNN (Convolutional Neural Network) is better. In simulational experiments, both types of cylinder can be distinguished perfectly, and two other types of satellite have around 90% probability to be classified. Rockets and defunct satellites can achieve 99% success rate in binary classification, but in further sub-classes classifications, the rate becomes relatively lower.