Some insights in novel risk modeling of liquefied natural gas carrier maintenance operations

This study discusses the analysis of various modeling approaches and maintenance techniques applicable to the Liquefied Natural Gas (LNG) carrier operations in the maritime environment. Various novel modeling techniques are discussed; including genetic algorithms, fuzzy logic and evidential reasoning. We also identify the usefulness of these algorithms in the LNG carrier industry in the areas of risk assessment and maintenance modeling.     

Enabling a viable technique for the optimization of LNG carrier cargo operations

In this study, we optimize the loading and discharging operations of the Liquefied Natural Gas (LNG) carrier. First, we identify the required precautions for LNG carrier cargo operations. Next, we prioritize these precautions using the analytic hierarchy process (AHP) and experts’ judgments, in order to optimize the operational loading and discharging exercises of the LNG carrier, prevent system failure and human error, and reduce the risk of marine accidents. Thus, the objective of our study is to increase the level of safety during cargo operations.     

Application of digital image correlation method to in-situ dynamic strain measurement

Application of digital image correlation (DIC) method to determination of in-situ dynamic strain is presented in this study. Firstly, an integrative software is programmed based on the DIC algorithms and point-wise least-squares fitting technique. Then, simulated speckle images are generated to study the computational accuracy of this software. The experimental setup and procedures for measuring in-situ dynamic strain through both DIC and strain gauge are proposed. The DIC results are close to those measured by strain gauge. This fact reveals that DIC is a practical and effective tool for in-situ dynamic strain measurement. Finally, the full-field in-situ dynamic strain of another specimen is measured by DIC, and the overall distribution of the strain in the measurement area is clearly shown.     

基于时延特性建模的多断面短时交通流预测

针对现有交通流预测方法未充分考虑多断面车流演变规律，提出基于时延特性建模的时空相关性计算方法. 该方法采用对不同断面、不同时刻交通流的分布相似性度量，对输入的车辆到达数据序列进行切割构建时空相似度矩阵，得到相邻断面之间的时延参数. 基于时延特性建模，将多断面之间的流量信息进行融合，使用长短时记忆(LSTM)网络进行流量预测. 通过对实际路段数据的预测和结果分析，验证所提方法的有效性和实用性.     

基于下游大水位变率的下水式垂直升船机随动技术的设计与实现

下游航道水位变率大,快速适应水位变化的准确停位随动技术,对下水式升船机的传动控制很重要.本文介绍下水式垂直升船机随动控制技术.首先,对控制对象的特性进行分析,描述了系统的速度运行曲线,对位置控制功能进行了研究.然后,搭建试验平台对本控制方案的性能进行了测试,给出了测试的方法和试验结果.实验结果表明本控制系统具有定位精度高、响应速度快等优点,能够适应下游大水位变化率的下水式垂直升船机准确停位要求.     

大跨度钢箱梁斜拉桥中跨合龙关键技术

以4座主跨超过400 m的钢箱梁斜拉桥中跨合龙控制为背景,对大跨度钢箱梁斜拉桥中跨合龙的2种方法进行对比分析,对合龙各主要工序的关键技术进行研究。提出了合龙段配切长度的计算公式和合龙口宽度连续观测的测点布置方式。建议:在调整好合龙口姿态后可不加压重,也可不采用临时劲性骨架锁定;采用无线采集设备采集合龙口结构的温度场,用激光测距仪测量合龙口宽度以提高观测效率和安全性;在悬臂施工阶段关注梁长累计误差并通过调整后续梁段的制造长度消除之。     

基于改进人工蜂群进化算法的移动机器人路径规划与仿真分析

针对经典人工蜂群算法在机器人路径规划中易于陷入局部极值,且寻优过程收敛速度较慢等问题,提出了一种基于约束优化的改进人工蜂群算法.通过设计变异算子来增大极值在陷入局部最优时的跳出概率,提高机器人路径规划的收敛能力.在机器人路径规划上,对文中方法、遗传算法、A*算法以及经典人工蜂群算法进行性能评估.实验结果表明,文中方法能有效避免路径规划中的局部极值,减少机器人路径规划时间损耗,提高了路径规划效率.     

The Teachable Moments on Marine Mammal Tours: Watching versus Swim-With Tours

With the continuing growth of the tourism industry over recent decades, has come a change in tourist behavior from the traditional stereotypical 3-S tourist (sun, sand, sex) to an increasingly sophisticated and demanding tourist. These “new” tourists like to learn about history, nature, and wildlife, and they expect an educational component on wildlife tours. This study investigated swim-with-dolphin tours in Kaikoura, New Zealand with regard to the educational content and the overall anatomy of these tours, using data from observations on a total of 32 tours during December 2011. The resulting data were then compared with the data from Hrycik and Forestell's study, which investigated the content of questions asked by passengers on whale-watching tours in Stellwagen Bank National Marine Sanctuary. Results of the on-tour observations indicate that the surveyed tours display a structured approach to interpretation, which is customized to the specific tour anatomy of a “swim-with” tour, and varies in some parts significantly from “watch-only” tour interpretation.     

Visualisation of uncertainty in probabilistic traffic models for policy and operations

This study investigates different methods to visualise uncertainty in static representations of probabilistic traffic models predictions on road-networks. Although various graphical cues may be used to represent uncertainty it is not a priori clear which of them are most suited for this purpose, since their legibility, intelligibility and the degree to which they interfere with other graphical elements in a representation differ widely. Several graphical uncertainty representations were therefore developed and analysed in expert sessions. A selection of the initial set of uncertainty visualisations was further evaluated in a cognitive alternative task-switching experiment. The results show that graphical representations are able to convey uncertainty information relatively accurately, while some uncertainty visualisations outperform others. It depends on the model and scenario which representation is most suited for a given application. This paper presents an overview of possible graphic uncertainty representations and the considerations involved when applying them to uncertainty in traffic model visualisations.     

Key technologies of ship remote control system in inland waterways under ship-shore cooperation conditions北大核心CSCD

［Objective ］ To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. ［Method］On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. ［Results］The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. ［Conclusions］The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.