转换层位置对高层建筑结构地震反应影响的研究

介绍了转换层结构的概念及国内外对转换层结构位置的研究现状,阐述了转换层结构分析的两种方法:振型分解反应谱法和动力时程分析法,运用这两种方法举例分析了转换层位置对结构自振周期、振型、地震反应力及分布等地震反应的影响,最后提出应按照规范要求限制转换层的设置高度,并适当加强转换层上下一至两层竖向构件的截面及配筋设计的建议。     

液舱旋转射流惰化模拟及优化

为探究气体惰化机理,提高惰化过程效率,对卧式椭球状LNG液舱的气体惰化过程进行数值模拟与优化。采用从椭球状液舱端部直流射流、旋转射流和混合射流的进气方式,分析气体射流流场结构和惰化效果,探究不同进气方式对惰化过程影响的机理,并提炼其惰化优化方案。结果表明：在进气流量一定时,旋转射流的惰化效果优于直流射流和混合射流,这是由于旋转射流会产生更大的进气扩张角,可大幅减少惰化死角的存在,有利于在储罐内部形成推移式惰化;旋转射流相对直流射流可节省40.4%氮气量和惰化时间,相对混合射流可节省26.2%氮气量和惰化时间。旋转射流优化方案可减少氮气耗量并节省惰化时间,提高惰化过程效率,具有较高的经济性,对于实际LNG液舱的气体惰化过程具有重要指导意义。     

船舶混合动力技术发展趋势分析

通过近年发布的《国际海事组织海运温室气体减排初步战略》等相关减排措施,提出船舶混合动力技术作为优选解决方式。介绍该技术发展背景,阐述其定义、架构及国内外发展应用现状,分析油电混合动力技术、气电混合动力技术的特点,对船舶混合动力技术发展趋势及应用前景进行展望,经调查研究,船舶混合动力推进系统具有操纵性好、效率高及特定工况排放低等特性,减排优势明显。     

燃气向心透平的非定常流动特性研究

以燃气为工质的向心透平常用于微型燃气轮机系统中,有着重要的工程应用价值。本研究关注燃气向心透平的非定常流动特性,基于一台功率等级为1MW,转速为30000rpm的燃气向心透平,首先进行了热力设计,得到了其关键位置的燃气工质热力参数及透平的模型尺寸。其次基于三维粘性数值模拟计算的方法,采用SST k-ω湍流模型及六面体结构化网格在商用软件CFX中对燃气向心透平进行了定常与非定常气动计算,详细分析了其气动特性及非定常流动状况。最终,分析了这一燃气向心透平的非定常气流激振力在时域及频域分布,并准确评估了其流量、扭矩、功率及效率等关键参数。     

海水-冰晶两相流非等温流动及传热研究

船舶在冰区航行时,存在冰晶颗粒混合海水流入船舶冷却系统现象。基于颗粒动力学理论,建立适用于海水-冰晶两相流的欧拉-欧拉双流体模型,耦合相间传热传质模型对海水-冰晶两相流在水平直管内流动及传热特性数值模拟。研究表明,冰晶颗粒流动过程中,在管道上部位置R=8~10mm处冰晶体积分数达到最大值,且随着速度增加而增大;当入口含冰率(IPF)为4%时,冰晶速度的最大值出现在管道中心轴线上方。当入口速度为1.0~3.0 m·s-1,含冰率4%~30%时,局部传热系数随入口速度及含冰率增大而增加。     

桥吊运输船的透气系统设计与分析

船舶舱室透气有各种不同的方式,尤其在特种运输船舶的设计中,通过对几种通常采用的透气方式进行走向,布局分析,结合在实际应用和透气系统本身的工作原理及规范要求研究,总结出各种方式的优缺点,为后来类似项目设计提供可参考和借鉴的依据,使设计优化,系统运行顺畅。     

喷孔位置对船用天然气发动机燃烧及排放影响的模拟研究

为了探究天然气与柴油喷孔位置对天然气发动机燃烧和排放的影响,基于L23/30天然气发动机,建立了柴油引燃天然气的发动机模型,利用CONVERGE软件对燃烧过程和排放进行模拟分析。模拟结果表明：由于天然气与柴油喷孔位置变化的影响,会导致柴油引燃天然气在空间的变化,因此对发动机的燃烧和排放造成了影响,通过对比不同喷嘴间的距离和不同喷嘴分布的设计方案得出,采用中心对称设计时获得了较好的燃烧和排放性能。     

无人粮食转运车车身刚强度分析

因有限元分析方法的不断成熟,使分析所得的结果准确度大幅提高,从而降低了研究成本,缩短了研发周期。基于这些特点,将有限元分析方法应用于各类车的设计研究。文章通过无人粮食转运车的结构特点,对该无人粮食转运车在四种典型工况下的刚度和强度进行了计算,分析了粮食转运车在这四种工况下运行时的位移变形量的最大值和应力最大值及其出现的位置,所得结果为新车型的车身骨架提供数据化参考。     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

Using GPS-data to determine optimum electric vehicle ranges: A Michigan case study

Fuel-switching personal transportation from gasoline to electricity offers many advantages, including lower noise, zero local air pollution, and petroleum-independence. But alleviations of greenhouse gas (GHG) emissions are more nuanced, due to many factors, including the car’s battery range. We use GPS-based trip data to determine use type-specific, GHG-optimized ranges. The dataset comprises 412 cars and 384,869 individual trips in Ann Arbor, Michigan, USA. We use previously developed algorithms to determine driver types, such as using the car to commute or not. Calibrating an existing life cycle GHG model to a forecast, low-carbon grid for Ann Arbor, we find that the optimum range varies not only with the drive train architecture (plugin-hybrid versus battery-only) and charging technology (fast versus slow) but also with the driver type. Across the 108 scenarios we investigated, the range that yields lowest GHG varies from 65 km (55+ year old drivers, ultrafast charging, plugin-hybrid) to 158 km (16–34 year old drivers, overnight charging, battery-only). The optimum GHG reduction that electric cars offer – here conservatively measured versus gasoline-only hybrid cars – is fairly stable, between 29% (16–34 year old drivers, overnight charging, battery-only) and 46% (commuters, ultrafast charging, plugin-hybrid). The electrification of total distances is between 66% and 86%. However, if cars do not have the optimum range, these metrics drop substantially. We conclude that matching the range to drivers’ typical trip distances, charging technology, and drivetrain is a crucial pre-requisite for electric vehicles to achieve their highest potential to reduce GHG emissions in personal transportation.