与燃油相关的新法规和新标准及其对船舶维修管理的影响

文章介绍了MARPOL73/78防污规则附则Ⅵ、欧盟2005/33/E中对船用燃油的要求和船用燃油标准ISO8217:2005。讨论了低硫燃油、燃油中的污染物对船舶设备可能造成的影响,并分析了燃油检测技术和滑油监测技术对避免燃油可能给柴油机造成的危害的作用。     

改烧重质燃油来降低运行成本

燃油价格的飞速上涨,造成船舶运输行业经营成本的剧增,特别对那些以轻质柴油为主要燃料船舶的船主和经营者更是雪上加霜,生产成本的剧增是企业处于艰难状态。如何应对这种情况是每一个经营者急需解决的问题。船舶改烧重质油,降低燃油费用是一项很好的方案。作者根据对柴油机燃油系统和燃烧过程的研究,结合实际工作经验,针对老船改烧重质油,较详细的论述了在船舶燃油系统设备改造中应注意的问题。     

船舶燃油应用技术

燃油费用在船舶运输成本中占很大的比例,约占50%。燃油的使用管理不仅直接影响船舶营运的效益,而且也影响船舶运行的动力性、可靠性。对设备的磨损、备件的消耗及机舱的维修保养工作起着至关重要的作用。为了做好燃油管理工作,不仅船舶机舱管理人员应熟悉船舶燃油应用技术,而且船舶公司机务管理人员、负责燃油采购人员甚至公司主管经理也应对船舶燃油应用技术充分地了解。     

欧盟0．1％低硫燃油法令2010年1月1日正式实行

欧盟委员会出台的个法令规定“从2010年1月1日起，所有在欧盟港口‘停靠’的船舶，其燃油含硫量不得超过0．1％的最高限制。”。该规定严格执行时间是2010年1月1日，但2010年1月1日到2010年7月1日将作为半年的执行缓冲期，从2010年7月1日开始，如挂靠欧盟港口船舶达不到欧盟规定的低硫燃油标准将被处罚，所有经营欧盟航线的船公司都应积极应对，提前做好准备。     

严格船舶排放控制区监督管理 实现空气质量改善和船运可持续发展双赢

正2月,上海市交通委、上海海事局发布了《关于上海港实施船舶排放控制区的通告》,规定自2016年4月1日起,上海市将要求船舶靠岸停泊期间使用硫含量≤0.5%m/m的燃油。此前,交通运输部颁布的《珠三角、长三角、环渤海(京津冀)水域船舶排放控制区实施方案》(以下简称"ECZ方案")要求于2017年1月1日起,包括上海港在内的11个核心港口区域内的船舶靠岸停泊期间应转用低硫油;有条件的港口可提前实施。     

云海轮加装船用燃油雾化电加热器节能效益评估

文章介绍了云海轮上加装中交水运行业船舶节能技术服务中心生产的新型燃油雾化电加热器的情况。实践证明,加装电加热器是解决船舶用劣质燃料油的好办法。     

燃油中催化剂颗粒对船舶柴油机的危害及对策

残留在燃油中的催化剂颗粒形成是燃油在炼制过程中不可避免的,这些残留在燃油中的催化剂颗粒,在柴油机运行中会造成喷油设备、活塞环、活塞头环槽、缸套、活塞杆、活塞杆填料函内刮油环及密封环的磨损加剧,从而造成系统油大量流失,严重时引发扫气箱着火等危害,给柴油机运行管理带来麻烦。对于及早发现残留在燃油中的催化剂颗粒对柴油机的危害,本文提出了行之有效的、切实可行的对策。     

燃油中催化剂颗粒对船舶柴油机的危害及对策

残留在燃油中的催化剂颗粒,在柴油机运行中会使喷油设备、活塞缸套、等运动部件磨损加剧,从而造成系统油大量流失,严重时引发扫气箱着火等危害,给柴油机管理带来麻烦。对于及早发现残留在燃油中的催化剂颗粒对柴油机的危害,本文提出了行之有效的、切实可行的对策。     

全球国家、地区竞争力排行榜（2010年）

快速增长的民用航空业正面临不断波动的航空燃油价格和燃油对环境造成负面影响的威胁。航空业正在探索各种能提高燃油效率、减少二氧化碳排放的方法，其中一个方法可能因此改变传统的能源模式，即研发生物类可再生航空燃油替代传统燃油，以减少二氧化碳排放从而减少污染。可以预见在不久的将来，生物燃油将会在航空公司运营中占有越来越重要的比例。     

远洋船舶供油单元辅助电加热装置

船舶供油单元燃油原来是由燃油/废气组合锅炉提供蒸汽加热,船舶正常负荷航行时,加热介质由废气锅炉产生蒸汽能满足加热燃油之需,停航与锚泊时由燃油锅炉产生蒸汽来满足燃油加热之需。供油单元加装辅助电加热装置后,船舶停航与锚泊时,在一定时间内(5~6天)由电加热装置替代燃油锅炉;在船舶航行期间,降速航行而导致废气锅炉蒸汽不足时由电加热替代锅炉燃烧产生加热介质保证燃油的温度,保证船舶正常航行,从而节约船舶能耗。     

Improving airline fuel efficiency via fuel burn prediction and uncertainty estimation

Reducing fuel consumption is a unifying goal across the aviation industry. One fuel-saving opportunity for airlines is the possibility of reducing discretionary fuel loading by dispatchers. In this study, we propose a novel discretionary fuel estimation approach that can assist dispatchers with better discretionary fuel loading decisions. Based on the analysis on our study airline, our approach is found to substantially reduce unnecessary discretionary fuel loading while maintaining the same safety level compared to the current fuel loading practice. The idea is that by providing dispatchers with more accurate information and better recommendations derived from flight records, unnecessary fuel loading and corresponding cost-to-carry could both be reduced. We apply ensemble learning techniques to improve fuel burn prediction and construct prediction intervals (PIs) to capture the uncertainty of model predictions. The upper bound of a PI can then be used for discretionary fuel loading. The potential benefit of this approach is estimated to be $61.5 million in fuel savings and 428 million kg of CO₂ reduction per year for our study airline. This study also builds a link between discretionary fuel estimation and aviation system predictability in which the proposed models can also be used to predict benefits from reduced fuel loading enabled by improved Air Traffic Management (ATM) targeting on improved system predictability.     

How much disruption to activities could fuel shortages cause? – The British fuel crisis of September 2000

In September of 2000 the UK experienced a blockade of oil refineries in response to rising fuel prices. These protests resulted in severe fuel supply disruptions that intensified over the course of about one week. During the peak of the crisis, travel activity by car was curtailed. This paper analyzes survey data collected about two months after the crisis utilizing the recent memory of respondents as to how they would expect this sort of disruption to affect their participation in daily activities. Specifically, we focused on a variety of non-discretionary and discretionary activities and examined what factors are associated with respondents expecting disruption to those activities. Statistical models were developed to analyze how demographic factors, commute mode selection, vehicle characteristics, and various other factors can explain how individuals expect disruption to their activities. Results suggest that the majority of individuals do not expect major disruptions, although for more car-dependent individuals, disruption was expected to be substantial, especially for work-related trips. These results have implications for the potential success and benefits of an integrated transport policy.     

Asymmetric responses of highway travel demand to changes in fuel price: An explanation via fuel price uncertainty

Previous research has examined asymmetric effects of fuel price uncertainty on energy demand. If we consider that energy demand is related to travel demand, the changes in fuel prices may have asymmetric effects on highway travel demand via fuel price uncertainty. In other words, when in general fuel price is steadily rising, the highway traffic volume decreases by a small percentage. On the other hand, the highway traffic volume increases by a large percentage when fuel prices are falling. We hypothesize that the uncertainty in fuel prices generates this kind of asymmetric effect on highway traffic volume in Korea. We use the Korean monthly fuel price and highway traffic volume data from 2001 to 2009, and define the intra-month (weekly) fuel price changes as monthly fuel price volatility which is a proxy for monthly fuel price uncertainty. We found that the direction of the change in fuel prices had asymmetric effects on highway travel demand and that the fuel price uncertainty led drivers to respond asymmetrically to the changes in fuel prices.     

Willingness-to-pay for infrastructure investments for alternative fuel vehicles

This study investigates potential demand for infrastructure investment for alternative fuel vehicles by applying stated preference methods to a Japanese sample. The potential demand is estimated on the basis of how much people are willing to pay for alternative fuel vehicles under various refueling scenarios. Using the estimated parameters, the economic efficiency of establishing battery-exchange stations for electric vehicles is examined. The results indicate that infrastructural development of battery-exchange stations can be efficient when electric vehicle sales exceed 5.63% of all new vehicle sales. Further, we find a complementary relationship between the cruising ranges of alternative fuel vehicles and the infrastructure established.     

Comparing rail fuel efficiency with truck and waterway

This paper presents a railroad energy efficiency model used to estimate the fuel economies for classes of trains transporting various commodities. Comparable procedures are used to estimate truck and waterway fuel consumption. The results show that coal unit trains are 4.5–5.0 times more energy efficient than movements in the largest trucks allowed in the eastern and western regions of the US, unit grain train movements in the central US are 4.6 times more fuel efficient, soda ash unit train and non-unit train shipments are 4.9 and 3.2 times more efficient, and ethanol unit train and non-unit train movements are 4.8 and 3.0 times more efficient. In terms of barge traffic, coal unit train and non-unit train are 1.3 and 0.9 times as energy efficient in the eastern US, grain unit train and non-unit train movements are 1.7 and 1.0 times more efficient from Minneapolis to the Gulf of Mexico, and grain unit train and non-unit train movements are 1.0 and 0.7 times more fuel efficient from the Upper Ohio River to the Gulf of Mexico.     

Heterogeneous consumer preferences for alternative fuel cars in China

This paper models consumer preferences for alternative fuel cars and conventional, petrol fueled cars in China. It compares discrete choice model specifications where each specification reflects how consumers choose between alternative fuel cars and conventional types of cars. We find that, in China, consumers differentiate between the types of alternative fuel cars and are more likely to consider switching from petrol fuel vehicles to hybrid than to electric cars. Segmentation analysis is used to explore groups of consumers and their likelihood of adopting alternative fuel cars.     

A network wide simulation strategy of alternative fuel vehicles

This paper presents an integrated simulator “CUIntegration” to evaluate routing strategies based on energy and/or traffic measures of effectiveness for any Alternative Fuel Vehicles (AFVs). The CUIntegration can integrate vehicle models of conventional vehicles as well as AFVs developed with MATLAB-Simulink, and a roadway network model developed with traffic microscopic simulation software VISSIM. The architecture of this simulator is discussed in this paper along with a case study in which the simulator was utilized for evaluating a routing strategy for Plug-in Hybrid Electric Vehicles (PHEVs) and Electric Vehicles (EVs). The authors developed a route optimization algorithm to guide an AFV based on that AFV driver’s choice, which included; finding a route with minimum (1) travel time, (2) energy consumption or (3) a combination of both. The Application Programming Interface (API) was developed using Visual Basic to simulate the vehicle models/algorithms developed in MATLAB and direct vehicles in a roadway network model developed in VISSIM accordingly. The case study included a section of Interstate 83 in Baltimore, Maryland, which was modeled, calibrated and validated. The authors considered a worst-case scenario with an incident on the main route blocking all lanes for 30 min. The PHEVs and EVs were represented by integrating the MATLAB-Simulink vehicle models with the traffic simulator. The CUIntegration successfully combined vehicle models with a roadway traffic network model to support a routing strategy for PHEVs and EVs. Simulation experiments with CUIntegration revealed that routing of PHEVs resulted in cost savings of about 29% when optimized for the energy consumption, and for the same optimization objective, routing of EVs resulted in about 64% savings.