大震地震序列自动地震速报结果分析——以云南漾濞6.4级和青海玛多7.4级地震为例

根据国家台网中心自动地震速报系统在云南漾濞和青海玛多2个地区的台网监测能力,选取2个地区2021年5月18—29日的地震序列,对自动地震速报系统进行性能分析。国家台网中心自动地震速报系统基本实现1min内的单路自动地震速报信息初次产出,根据地震台网密度的不同,产出时间从30～60s不等。与地震编目结果相比,云南漾濞地震序列震中位置偏差较小,青海玛多地震序列震中位置偏差较大,2个地震序列震级偏差不大。青海玛多地震序列震中位置偏差较大的原因是该区域台站稀少且空隙角较大。自动地震速报系统存在少量的漏报地震,与系统定位时信噪比较低、台站空隙角较大及多个地震混叠在一起有关。     

位移和最大相关距离在ECMWF集合预报产品中的应用

文章提出了一种对集合预报产品进行自动划分的新方法, 即位移和最大相关距离。 其基本假定是集合预报成员在一定程度上代表了未来可能发生的某类天气形势, 为此引入了天气类型的概念, 并以法国中期预报员总结出的影响法国的 5 类天气形势为基础, 对欧洲中期天气预报中心(以下简称 ECM WF)的集合预报产品进行了划分。结果表明, 大气的可预报性与预报时效、预报的天气有关。 该文提出的新方法简洁直观, 便于使用, 在天气类型和实际天气之间建立了最直接的联系, 大大压缩了集合预报产品的信息量。 ECM WF 的集合预报产品对影响法国的平直型、热阻塞型、冷阻塞型、扰动型等天气形势预报效果比较好, 而对波动型则效果稍差。     

AW11型自动气象站的原理及应用

本文介绍一种新型的自动气象站，它是针对小机场、直升机场和无人值守的飞机跑道而设计的独立天气观测和报告系统，可以测量全部标准的航空天气参数和生成精确实时的天气报告。     

浮子水位、雷达水位双备份观测系统设计

珠江口水文信息系统的水文观测站都是无人站, 采用的均是浮子式水位计, 且数量逐年增多, 发生故障后, 修复时间长, 造成数据缺测。为了解决这个问题, 本文提出使用浮子水位、雷达水位双备份观测方式, 数据中心可以通过人工干预或系统自动智能诊断方式分时间段分别从浮子水位、雷达水位中挑选数据作为该站点的实际连续观测数据。本文阐述浮子水位和雷达水位双备份观测的实时数据传输系统组成及工作原理, 并通过对浮子水位、雷达水位观测数据的对比分析, 验证数据中心通过这种分时间段组合挑选的数据具有连续性、有效性, 可作为观测站的实际观测数据, 浮子水位、雷达水位双备份观测系统可以应用在珠江口水文信息系统或类似观测领域。     

Application of artificial intelligence techniques in automatic hull form generation

The paper describes a methodology for automatic hull form generation of ships with some desired performances using artificial intelligence techniques. The whole implementation process is divided into three main components. First of all the half-breadth weight matrices are generated that would provide population with pre-fitness by examining the relationship of the hull form with the principal dimensions of a number of existing vessels. Secondly, breadth and draft are adjusted using Neural Network Concepts. Breadth, draft, length, displacement and speed of the ship are very related terms and relations among them create some constraints. Neural Networks solve these constraints and adjust the parameters. Finally, Genetic Algorithm is used for searching the exact solution by examining several generations. For this, the algorithms need to measure fitness for every population in every generation. Unfortunately, GA doesn't guarantee fairness of the surface of the hull form, which can't be ignored. So, for every population especially for newborn population fairing techniques would be used. However, being complex geometric shape, hull form surface can't be faired using least-square or other single equation fitting techniques. Fairness is done taking pair-wise points using B-spline functions [CAD 20(1988)].     

应用层次分析法确定道路属性指标的权重

在车辆导航系统的路径规划中,如何标定道路权重是一个很重要的问题,本文应用层次分析法(AHP),对道路元素的各种属性指针进行加权,获得了较切合实际的指针权重结果,为车辆导航系统中的路径规划提供更准确的结果,使获取的最优路径更切合实际。     

MFSK水声通信接收系统中的幅度均衡设计

为了抗幅度随频率的衰减，提出了一种基于多频移频健控（MFSK）调制方式的水声通信接收系统中的幅度均衡技术，介绍了构成幅度均衡电路的基本原理以及在厦门港浅海域中的实验结果，实验结果表明，该技术能有效克服上系统中的信号民幅度随率的衰减问题。使接收到的图像清晰易读。     

Service vessel activity in the U.S. Gulf of Mexico in support of the oil and gas industry using AIS data, 2009–2010

Offshore exploration and production in the U.S. Gulf of Mexico is supported by a large number of service vessels characterized by complex logistical patterns and demand points distributed across an expansive geographic area. No quantitative data on the spatial and temporal distributions of service vessel activity in the region is available due to the size, complexity and dynamics of the network. The purpose of this paper is to apply Automatic Identification System position data to quantify service vessel activity in the U.S. Gulf of Mexico from 2009 to 2010. A total of 1.1 million vessel arrivals and departures were recorded in 2009–2010, and in 2010, the number of vessel events increased by 40% due in part to the Macondo oil spill and cleanup response. Port-to-port movements comprise the majority of events and about 30% of activity relates to movements offshore. Port Fourchon, Venice, New Orleans, Sabine-Neches, and Lake Charles were the most active ports during the period. A detailed breakdown of vessel counts and the limitations of the analysis are outlined.     

Automatic collision avoidance of multiple ships based on deep Q-learning

As the number of ships for marine transportation increases with the globalisation of the world economy, waterways are becoming more congested than before. This situation will raise the risk of collision of the ships; hence, an automatic collision avoidance system needs to be developed. In this paper, a novel approach based on deep reinforcement learning (DRL) is proposed for automatic collision avoidance of multiple ships particularly in restricted waters. A training method and algorithms for collision avoidance of ships, incorporating ship manoeuvrability, human experience and navigation rules, are presented in detail. The proposed approach is investigated not only by numerical simulations but also by model experiments using three self-propelled ships. Through the systematic numerical and experimental validation, it is demonstrated the developed approach based on the DRL has great possibility for realising automatic collision avoidance of ships in highly complicated navigational situations.     

Multiphysics implementation of advanced soil mechanics models

Using multiphysics computer codes has become a useful tool to solve systems of partial differential equations. However, these codes do not always allow for the free introduction of implicitly defined state functions when automatic differentiation is used to compute the iteration matrix. This makes it considerably more difficult to solve geomechanical problems using non-linear constitutive models. This paper proposes a method for overcoming this difficulty based on multiphysics capabilities. The implementation of the well-known Barcelona basic model is described to illustrate the application of the method. For this purpose, without including formulation details addressed by other authors, the fundamentals of its implementation in a finite element code are described. Examples that demonstrate the scope of the proposed methodology are also presented.