消声器内部流场及其对消声性能影响

在自行设计建造的消声器静态试验台上,对某型消声器在有、无气流两种情况下进行了试验研究,并根据试验进行了消声器内部流场CFD仿真研究。研究表明,气流在一定的速度范围内对消声器消声量影响很小,当超出范围时消声量随气流速度的增大而减小,同时消声器压力损失也加大。说明流速和内部结构是影响消声器性能的重要因素。     

SHT-2000灭火系统及其在地铁工程中的应用

对目前地铁中使用的哈龙(Halon)1301、FM200、烟络尽(Inergen)等气体灭火系统与一种新型气体灭火系统--SHT-2000型进行比较.介绍了SHT-2000型气体灭火系统的技术特点和优良性能.详细说明了气体型灭火检验标准与要求.指出SHT-2000型全淹没灭火系统是当前对Halon 1301的最佳替代品,这是一种适用于地铁工程的新型气体灭火技术.     

南京地铁1号线的气体灭火设计

结合南京地铁1号线的工程设计,将七氟丙烷(HFC-227)气体消防工程设计中经常遇到的一些问题,如管网设计距离、系统管网的管道内容积、七氟丙烷的喷放时间等,在满足技术规范要求的前提下所采取的解决方案做了阐述.这些方法的使用大大缩短了工程设计时间.介绍了南京地铁1号线报警灭火系统的结构,气体灭火系统与车站火灾报警系统的通信方案.     

城市公共加油站规划技术要求

针对国内目前涉及公共加油站规划管理的标准和研究文献较少,且针对性不强、管理尺度不一的问题,采用调查论证、定性分析、定量分析和经验总结的方法,对现有标准和文献存在的问题进行分析,并对广州地区近10年加油站规划、管理的实践经验进行总结.系统探讨城市公共加油站在选址定点、空间布局、用地面积以及内部平面布置等方面的技术要求,以建立与城市发展相适应、布局合理、竞争有序、功能完善的现化化加油站销售服务网络体系.     

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。     

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。     

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.