基于多星融合高度计数据的中国海波浪能资源评估

Wave energy resources are abundant in both offshore and nearshore areas of the China's seas. A reliable assessment of the wave energy resources must be performed before they can be exploited. First, for a water depth in offshore waters of China, a parameterized wave power density model that considers the effects of the water depth is introduced to improve the calculating accuracy of the wave power density. Second, wave heights and wind speeds on the surface of the China's seas are retrieved from an AVISO multi-satellite altimeter data set for the period from 2009 to 2013. Three mean wave period inversion models are developed and used to calculate the wave energy period. Third, a practical application value for developing the wave energy is analyzed based on buoy data. Finally, the wave power density is then calculated using the wave field data. Using the distribution of wave power density, the energy level frequency, the time variability indexes, the total wave energy and the distribution of total wave energy density according to a wave state, the offshore wave energy in the China's seas is assessed. The results show that the areas of abundant and stable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, southeast of Taiwan in the China's seas; the wave power density values in these areas are approximately 14.0–18.5 k W/m. The wave energy in the China's seas presents obvious seasonal variations and optimal seasons for a wave energy utilization are in winter and autumn. Except for very coastal waters, in other sea areas in the China's seas, the energy is primarily from the wave state with 0.5 m≤H s≤4 m, 4 s≤T e≤10 s where H s is a significant wave height and T e is an energy period; within this wave state, the wave energy accounts for 80% above of the total wave energy. This characteristic is advantageous to designing wave energy convertors(WECs). The practical application value of the wave energy is higher which can be as an effective supplement for an energy consumption in some areas. The above results are consistent with the wave model which indicates fully that this new microwave remote sensing method altimeter is effective and feasible for the wave energy assessment.     

Validating RAPFISH sustainability indicators: Focus on multi-disciplinary aspects of Indian marine fisheries

In determining the importance of fisheries sustainability indicators, stakeholders’ interest plays a defining role in the fisheries management practices. The indicator based tools such as RAPFISH have been available for sustainability assessment of fishery resources. In the present study, procedures to validate the pre-selected RAPFISH, which is a multidisciplinary indicator based evaluation tool for measuring the sustainability of fishery resources, are applied. The sustainability indicators were subjected to validation process based on feedback from resource owners, users and experts, using Multi-Criteria Analyses such as Weighted Sum Model and Analytic Hierarchy Process. Based on the validation results, suggestions have been made to improve methodology and its effective application in practice. This paper demonstrates RAPFISH as a potentially effective multidisciplinary tool for evaluation of sustainability of fishery resources.     

道路网络示意图的多边形生长算法

道路网络示意图是实体网络的抽象表示,因其更加符合人的认知习惯,在地图服务与地图制图领域已得到初步应用。以路径为单位的网络示意图自动生成算法只顾及节点与线段的局部布置,且较难以维护网络拓扑一致性。本文以闭合多边形(网眼)为基本单位,利用网眼的独立性与邻接性,提出了多边形生长算法,核心思想是将道路网络分类为闭合多边形与非闭合线段,以闭合多边形提取、映射、优化为主线,辅助组合非闭合线段。算例分析验证,本算法在网络均衡分布及拓扑一致性方面具有优势。     

基于时空轨迹数据的传染病传播风险评估

本文利用CRAWDAD提供的2009年10月份纽约市的出租车时空轨迹数据,依据复杂网络理论在城市交通网络中的应用,提出了一种方法求解出租车空间密度表示移动人群的时空密度变化,并用不同时段的平均速度表示人群的移动速度综合判定传染病在市内传播的高风险区域,重点分析了13时传染病传播的风险区位。通过建立空间密度与平均速度的二维特征空间,并将齐夫定律与能够遍历曼哈顿区的最大速度作为条件确定传染病传播的风险边界。结果反映在二维特征空间中,由最大遍历速度、安全行驶的空间密度临界值与数据上边界围成的三角区内节点对应的实际区位为传染病传播的高危区域。     

三维激光扫描点云混合像素的自动识别方法

混合像素的存在会给点云后续处理与应用带来干扰,针对如何在原始扫描点云中自动识别混合像素的问题,从扫描仪的工作原理着手分析了混合像素的形成条件,结合扫描仪的内部光电转换机制与真实扫描数据论证混合像素的测距误差分布规律,据此设计混合像素的自动探测方法。利用真实原始扫描数据进行实验,结果证明,文中方法能够准确地识别出点云中的混合像素。     

基于概率密度演化的基础隔震结构随机响应分析

针对抗震结构和基础隔震结构,应用概率密度演化方法对其进行多遇地震作用下的线性随机响应分析。通过引入工程地震动物理随机函数模型,采用数论选点法对多维外荷载随机变量进行离散代表点的生成并求得其赋得概率,利用离散代表点合成地震动加速度时程样本作为输入结构的随机激励,对于每条地震波,相当于对结构进行确定性动力反应分析。在求得结构响应及其相关导数后,应用TVD差分格式求解广义概率密度演化方程即可得到所求响应的时变概率密度及其演化。结果表明：基础隔震结构在随机地震作用下相比抗震结构具有良好的减震性能,隔震层的设置能够减小结构位移响应的标准差,减少了结构响应的离散型;概率密度演化方法不仅能够给出结构响应的二阶统计矩,还能全面地反映结构响应的时变概率信息,位移响应的概率密度函数分布不服从正态分布或其他常用分布,且随着时间演化。     

中国地震预警延迟时间算法及其对预警盲区的影响研究

通过分析预警系统的预警步骤来探讨影响获得预警时间的因素,并与瑞士地震台网预警延迟各步骤进行对比,得出中国地震预警系统仪器延迟时间为7.6s。提出地震波到台站所需时间的算法,较震中假设在台站中间的传统算法更为准确,在此算法下采用双台法和四台法计算接收地震波所需时间,得到中国地震预警延迟时间。讨论双台法和四台法在不同震源深度和台站密度下对预警盲区大小的影响,在台间距小于20km时,2种方法预警盲区差异不大。通过理论计算得出,在台站到达一定密度时,预警系统仪器延迟时间缩短比台站加密对预警盲区的缩小更有效。     

若羌测震台背景噪声分析

若羌测震台属国家测震台,为了评估该台站背景噪声水平,采用Welch平均周期法,对2009—2019年共11年近5 000条小时波形数据进行功率谱计算,分析异常噪声特征。同时,绘制该台站11年无断记数据概率密度函数图,分析整体噪声水平。分析发现:①若羌测震台受持续增加的人类活动影响,背景噪声水平不断升高;②受气压影响,水平向噪声水平明显高于垂直向;③2017年后,若羌测震台功率谱密度曲线在频率10 Hz附近出现高频异常,应为米兰河水库运行造成的固有干扰。     

山东数字测震台站台基背景噪声分析

介绍了山东数字地震台网基本情况,计算了40个测震台站台基背景噪声,利用Welch方法计算噪声功率谱密度（PSD）,进而计算地震台台基1—20 Hz地动噪声均方根值（RMS）和有效动态观测范围。根据计算结果,依照《地震台站观测环境技术要求》,对山东测震数字台网40个参评测震台站进行背景噪声级别分类,并分析不同台站背景噪声水平较低的原因,以期为测震台网的优化建设提供数据支持。     

Fission track and fault kinematics analyses for new insight into the Late Cenozoic tectonic regime changes in West-Central Sulawesi (Indonesia)

A 3-D density model for the Cretan and Libyan Seas and Crete was developed by gravity modelling constrained by five 2-D seismic lines. Velocity values of these cross-sections were used to obtain the initial densities using the Nafe–Drake and Birch empirical functions for the sediments, the crust and the upper mantle. The crust outside the Cretan Arc is 18 to 24 km thick, including 10 to 14 km thick sediments. The crust below central Crete at its thickest section, has values between 32 and 34 km, consisting of continental crust of the Aegean microplate, which is thickened by the subducted oceanic plate below the Cretan Arc. The oceanic lithosphere is decoupled from the continental along a NW–SE striking front between eastern Crete and the Island of Kythera south of Peloponnese. It plunges steeply below the southern Aegean Sea and is probably associated with the present volcanic activity of the southern Aegean Sea in agreement with published seismological observations of intermediate seismicity. Low density and velocity upper mantle below the Cretan Sea with ρ  3.25 × 10³ kg/m³ and V_p velocity of compressional waves around 7.7 km/s, which are also in agreement with observed high heat flow density values, point out at the mobilization of the upper mantle material here. Outside the Hellenic Arc the upper mantle density and velocity are ρ ≥ 3.32 × 10³ kg/m³ and V_p = 8.0 km/s, respectively. The crust below the Cretan Sea is thin continental of 15 to 20 km thickness, including 3 to 4 km of sediments. Thick accumulations of sediments, located to the SSW and SSE of Crete, are separated by a block of continental crust extended for more than 100 km south of Central Crete. These deep sedimentary basins are located on the oceanic crust backstopped by the continental crust of the Aegean microplate. The stretched continental margin of Africa, north of Cyrenaica, and the abruptly terminated continental Aegean microplate south of Crete are separated by oceanic lithosphere of only 60 to 80 km width at their closest proximity. To the east and west, the areas are floored by oceanic lithosphere, which rapidly widens towards the Herodotus Abyssal plain and the deep Ionian Basin of the central Mediterranean Sea. Crustal shortening between the continental margins of the Aegean microplate and Cyrenaica of North Africa influence the deformation of the sediments of the Mediterranean Ridge that has been divided in an internal and external zone. The continental margin of Cyrenaica extends for more than 80 km to the north of the African coast in form of a huge ramp, while that of the Aegean microplate is abruptly truncated by very steep fractures towards the Mediterranean Ridge. Changes in the deformation style of the sediments express differences of the tectonic processes that control them. That is, subduction to the northeast and crustal subsidence to the south of Crete. Strike-slip movement between Crete and Libya is required by seismological observations.