碎冰条件下单点系泊船舶动态响应特性研究

为了研究不同单点系泊位置对极地系泊船舶在来冰角度改变时动态响应的影响,运用离散元方法(DEM),计算了船舶在60%密集度下,冰速为1.0 m/s、冰厚为1 m时不同角度的船冰阻力,结合系泊分析软件二次开发功能,计算分析系泊船舶在不同来冰角度和不同系泊位置下受上述冰情影响下的响应。通过对模拟结果与试验结果的对比,认为离散元方法(DEM)的数值模拟结果与试验结果吻合较好;单点系泊位置为距船头L/4时,系泊船舶能以最快速、最稳定的方式对来冰方向的变化做出响应。     

深海滑坡灾害的物质点法模拟

深海滑坡可以沿着斜坡搬运大量沉积物,是危害巨大的海洋地质灾害之一。评估深海滑坡的流滑机制并量化分析其对海底结构物的冲击对海洋资源的开发利用至关重要。采用物质点法对滑坡的滑动特性进行了总应力分析。设计了三组不同的土体、海床参数,展现了三种不同的滑动形态:延展、块体和扩张。随后复现了流滑体对部分暴露管线的冲击过程,并对冲击力的稳定值进行了分析,分析中考虑了流滑体的惯性、抗剪强度和静压力的影响。研究表明,物质点法能够用于模拟深海滑坡的流滑过程及其对海底结构物的冲击,可以为海洋工程中的实际设计工作提供服务。     

考虑冲刷影响的筒型基础竖向极限承载力研究

大直径宽浅式筒型基础,阻水宽度大,在位工作期间受波浪海流作用,其周围土体易被冲刷。为研究单侧地基土体受冲刷后筒型基础的竖向极限承载力变化,通过引进冲刷率的概念,采用有限元方法研究了不同冲刷率下筒型基础的竖向极限承载力;并基于Meyerhof理论建立了计算不同冲刷率下筒型基础竖向极限承载力的极限平衡方法。研究结果表明,随着冲刷率增大,筒型基础的极限承载力出现不同程度的下降,当冲刷率为0.8时,即筒型基础单侧土体冲刷深度达6.4 m时,筒型基础的竖向极限承载力折减率为3.28%。建立的极限平衡算法可准确计算冲刷条件下筒型基础的竖向极限承载力。     

基于激波捕捉类Boussinesq模型对岛礁地形上波浪传播的数值模拟

为了探究激波捕捉类Boussinesq模型在模拟岛礁地形上规则波和不规则波传播的可行性,采用基于完全非线性Boussinesq方程并具有激波捕捉能力的数值模型Funwave-TVD对规则波和不规则波在岛礁地形上的传播进行了数值模拟,通过与试验数据对比,分析模型中空间步长的影响,验证模型在模拟波高、平均水位分布以及波谱空间演变的能力,结果表明:采用合适的空间步长,模型能较好地模拟规则波和不规则波在岛礁地形上的传播和演化过程。对于规则波,较小的空间步长可改善破碎点处波高峰值的预测,并能更好地预测波浪破碎后波高的空间分布,相比结合经验破碎的Boussinesq模型,Funwave-TVD能更好地模拟规则波在岛礁地形上的破碎,以及破碎以后行进涌波的再生成过程;对于不规则波,Funwave-TVD总体而言能较好地模拟涌浪有效波高、次重力波的生成及空间演化和平均水位,但会低估礁坪上次重力波波高,较粗的空间步长也会低估礁坪上涌浪有效波高。     

一种海洋混合层深度的智能识别方法研究

文章提出了一种识别混合层深度的人工智能方法。该方法在温度(密度)与压强(或深度)间建立线性模型, 并且将其系数和方差做成一组表征廓线特征的统计量。初始时为模型设定一个主观的先验分布, 在一个自海表向下移动的窗口内通过贝叶斯链式法则和最小描述长度原理学习新数据, 得到系数均值的最大后验概率估计。用F-检验识别系数发生突变的位置, 以此确定混合层的存在性及其深度。通过2017年2月太平洋海域的地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography, ARGO)数据进行测试, 并且以质量因子(Quality Index, QI)值作为判断识别混合层深度结果准确性的依据, 发现该方法相比于梯度法、阈值法、混合法、相对变化法、最大角度法和最优线性插值法在识别结果上具备更大的QI值。表明该方法能够准确识别混合层深度。     

含沙浑水体的黏度测量及应用分析

含沙浑水体的高速冲击会对海底构筑物造成破坏,在计算浑水体对构筑物的作用力时,黏度是一项重要参数。本文利用落球试验和流变仪测试试验,测定了不同浓度含沙浑水体的黏度,给出其起始黏度与动力作用后的稳定黏度。结果表明:含沙量在大于400g/L时,浑水体为可用赫巴模型描述的非牛顿流体,并可简化为宾汉体;在含沙量小于400g/L时,浑水体仍可用宾汉体模型描述,在忽略较小的初始剪切应力时,可简化为牛顿流体。浓度大于400g/L的浑水体的起始黏度约为稳定黏度的100倍。文中讨论了含沙浑水体起始黏度与稳定黏度在工程计算应用中的适用情况。     

Bathymetry,substrate and fishing areas of Southeast Atlantic high-seas seamounts

Most of the Southeast Atlantic Ocean is abyssal, and global bathymetries suggest that only ～3.2% of the areas beyond national jurisdiction (ABNJ; also known as the high seas, as defined in the United Nations Convention on the Law of the Sea [UNCLOS]) are shallower than 2 500 m. This study mapped bathymetry and characterised substrates in selected seamount summit areas, including several that have been or may become fishing areas. The southernmost location, the Schmitt-Ott Seamount, has exposed volcanic bedrock with surrounding flats covered by thin biogenic sediments and/or coral rubble that appears ancient. At Wüst, Vema, Valdivia and Ewing seamounts the basaltic base appears to be overlain by coral caps and other coral substrates (sheets, rubble). Adjacent summit plains have biogenic sediments of varying thickness. Vema has a flat, roughly circular summit, <100 m deep, with the shallowest point being a 22-m-deep summit knoll; the upper slopes have ancient coral framework, but the summit has a mixture of coralline and volcanic rock and coarse sediments, including extensive areas with coralline algae and kelp forests. Valdivia Bank is a 230-m-deep, flat, rocky area (～11 × 5 km), protruding steeply from the extensive multi-summit Valdivia subarea of the Walvis Ridge. The distribution of past fisheries in the Convention Area of the South East Atlantic Fisheries Organisation (SEAFO) was considered in relation to the new information on bathymetry and substrate.     

An integrated approach to assess the ecological and chemical status of lakes with HOD/AHOD: a case study of two lakes

The thermal strati?cation of the lakes impedes the transfer of atmospheric oxygen into the lower layers of the lake. In lakes which are af fected by diverse anthropogenic in?uences, the increasing organic matter amounts lead to a sharp decrease in hypolimnetic oxygen amounts, aided by thermal strati?cation,and anaerobic conditions arise. The determination of hypolimnetic oxygen demand(HOD) and areal hypolimnetic oxygen demand(AHOD) and their monitoring represent an integrated approach to investigate the oxygenation of lakes, the nutrient conditions, and the physicochemical dynamics. In this study, two lakes dif fering by size and af fected by dif ferent anthropogenic sources, are investigated in this respect. At?rst, bathymetric studies were conducted to determine the depth, surface area, and volume relationships.Then, based on monitoring studies conducted in 2013 and 2014, the thermal strati?cation dynamics and layer properties were established using the relative thermal resistance to mixing(RTRM) index based on temperature and density pro?les. Following this, the oxygen depletion rates were determined by oxygen and temperature pro?ling in the hypolimnion. For the years of 2013 and 2014, the AHOD values for the Borabey Pond which is far from anthropogenic in?uences, were found to be 0.848 and 0.569 g O 2/(m·d), respectively.The AHOD values for the Porsuk Reservoir which was overburdened for years by industrial and domestic pollution were found to be 4.263 and 5.099 g O 2/(m·d), larger than its counterpart by almost sevenfold. The HOD and AHOD monitoring can be considered to a valuable tool for assessing the ecological and chemical status of lakes within Annex 5 of the Water Framework Directive and as an integrated approach to assess and monitor the status of lakes.     

面向双/多变量的连续面域拓扑图可视化方法

面域拓扑图是一种利用区域面积大小定量表达区域属性信息的可视化方法。由于其区域面积本身已经表示某一变量,因此这更有利于双/多变量的制图表达。针对目前基于面域拓扑图的双/多变量表达方法中存在的难以表达相邻区域之间基本状况和不利于不同地理现象的空间分布规律及差异表达的问题,本文提出一种面向双/多变量的连续面域拓扑图可视化方法。首先通过格网密度补偿和积分步长逐步试探的方法对基于扩散模型的连续面域拓扑图生成算法进行部分优化,完成基本变量的表达,然后分别通过空间内插和符号扩展完成第2和第3变量在连续面域拓扑图中的表达。最后以慕尼黑市人口密度和银行/ATM分布(双变量)数据以及奥格斯堡市人口密度数据、幼儿园分布以及规模数据(多变量)为试验数据进行可视化,并通过实证分析验证了该方法的有效性和优越性。     

高分辨率光学遥感场景分类的深度度量学习方法

针对高分辨率光学遥感影像场景具有同类型内部差异大、不同类型间相似度高导致部分场景识别困难的问题,本文提出了一种深度度量学习方法。首先在深度学习模型的特征输出层上为每类预设聚类中心,其次基于欧氏距离方法设计均值中心度量损失项,最后联合交叉熵损失项以及权重与偏置正则项构成模型的损失函数。该方法的目标是在特征空间上使同类型特征聚集并扩大类型间的距离以提高分类准确率。试验结果表明,本文方法有效地提升了分类准确率。在RSSCN7、UC Merced和NWPU-RESISC45数据集上,与现有方法相比,分类准确率分别提高了1.46%、1.09%和2.51%。