模块化救生装置的研制

根据集装箱船加改装成医院船工作中的需要,为满足船上人员海上遇险救生需要,研制了模块化的救生装置。针对模块化医院船的特点,提出担架伤员撤离主要通过救生艇,并对救生艇模块的设计进行了详细的说明,还介绍了海上撤离系统和气胀式救生筏。通过海上试验,证明该套救生装置可顺利地在集装箱船上安装和使用,可有效满足医院船的人员海上遇险救生需要。     

EH47高强度厚钢板角焊缝裂纹修补工艺研究

随着造船业飞速发展,大量高厚度、高强度、高韧性的钢板被应用于大型集装箱船的上甲板区域。EH47是工业革新的最新成果,它的屈服强度高,被使用于万箱级集装箱船的上甲板区域。某船厂10000 TEU船舱口围钢板与舾装件角焊缝发生开裂,通过有限元计算出裂纹发生的可能性,并分析了开裂发生的原因,针对结构特点和材料特点,采用CO2气体保护焊焊补,通过选用合理的焊丝、预热温度、焊后保温等措施来防止裂纹的产生。     

三峡库区1000t应急抢险打捞起重船的开发设计

本文阐述了708所为长江航道局开发设计的一艘1000吨应急抢险打捞起重船,主要用于长江三峡库区应急抢险的沉船沉物起重打捞,兼顾长江中游河段应急抢险打捞的需要,三峡库区和长江中游干线特定的水域环境、库区船闸尺度及跨江桥梁高度限制决定了本船在船型和主尺度、起重机及其搁架形式、定位方式、压载系统、打捞作业系统配置等方面都有独特的考虑。     

长江干线集装箱吞吐量分析预测

港口集装箱吞吐量是进行港口规划和加强港口建设的依据,预测长江干线主要港口企业集装箱吞吐量对促进长江干线水域经济发展发挥了重要作用。以长江干线主要港口企业集装箱吞吐量为基础,分析二次指数平滑法、灰色模型预测法和BP-GA算法的原理,分别建立三种相应的预测模型并比较预测结果及精度。结果表明BP-GA模型能更加准确预测集装箱吞吐量在时间序列上的变化趋势,预测拟合度最佳。最后以该模型预测分析2021年1月至12月的长江干线主要港口企业集装箱吞吐量,为未来长江航运发展提供参考。     

2750TEU集装箱船局部振动评估

针对2 750 TEU集装箱船,在船体总振动评估的基础上,采用经验公式及有限元法,对液舱及上层建筑的局部振动进行详细评估,并根据不同区域的计算结果采取相应的改进措施.     

Cargo ship aft panel stresses prediction by deconvolution

This article introduces novel extreme value prediction method that can be used for a variety of offshore engineering applications. First, to demonstrate the novel method, fictitious data from a non-linear Duffing oscillator and measured wave heights were used as examples. The second incident included a container ship that experienced significant deck panel strains while traveling across the Atlantic Ocean in bad weather. The main concern for cargo ship transportation is potential loss of container owing to violent movements. It is challenging to model such a situation because waves and ship motions are both non-stationary and complicatedly nonlinear. Extreme motions greatly increase the role of nonlinearities, activating effects of second and higher order.Furthermore, due to the scaling and the choice of sea state, laboratory testing may also be called into doubt. Therefore, data collected from actual ships during difficult weather voyages offers a special perspective on the statistics of ship motions.This paper aims to highlight an alternative method of extrapolation that is based on intrinsic properties of the data set itself and does not assume any extrapolation functional class. Extreme value predictions typically originate from certain statistical distribution functional classes to fit the data and then extrapolate. Engineering design can make use of the unique extrapolation method that has been proposed. The proposed method's forecast accuracy has been verified in comparison to the Averaged Conditional Exceedance Rate (ACER) extrapolation method.