跑道不停航施工组织的数学建模与求解

跑道不停航加铺工程要求在较短的施工周期内完成多项关键施工工序的实施,受到时间周期、资源利用、工序完整性等多方面的制约,因此,科学合理的施工组织方案对于确保工程质量意义重大。该文充分考虑了跑道不停航施工的各种制约因素,分析测算了各道工序的施工时间,基于最优化方法原理,通过施工组织网络图建立了不停航施工组织优化的数学模型。该模型能够灵活地根据所选决策变量定量求解出施工周期内的施工能力,根据时间和资源两方面的约束条件给出资源的合理配置,可为相似工程编制合理的施工组织方案提供参考。     

输运流体海洋立管的动力特性

从流体的动量方程出发,考虑流体和管道的耦合,推导出输运流体海洋立管的偏微分运动方程。用Hermite插值函数和Galerkin法离散运动方程建立海洋立管动力运动的有限元模型。然后,利用该模型研究管内气柱流对固有频率的影响。计算结果表明:立管内出现气柱流时,固有频率随气柱位置的不同而明显变化。     

混合对转推进系统设计与实船应用研究

为全面深入了解混合对转推进系统实船安装对船舶性能影响,为数值仿真和性能预报提供实船参考数据,以集装箱运输船为应用对象,提出了一种把吊舱推进器集成在挂舵臂上的混合对转推进系统(CRP-POD),详细阐述了CRP-POD的系统构成、工作模式和电气控制系统实船设计方案。通过实船试验和运行数据分析,安装混合对转推进系统的船舶与同系列安装常规推进系统的船舶相比,特定航行工况下航速有2~3%的提升、回转能力有所降低、航向稳定性上优于常规船。     

美国海军核潜艇舱室大气监测主分析仪器发展述评

舱室大气监测系统是核潜艇的重要组成部分之一,其运行效能直接影响舱室设备可靠运行、人员安全和健康。本文对美国核潜艇的大气监测技术的研究和应用情况进行了详细论述,重点介绍了已装艇应用近半个世纪的中央大气监测系统(Central Atmosphere Monitoring System,CAMS),以及近年来的最新技术探索。当前大气监测技术仍然难以完全满足核潜艇舱室大气监测需求,迫切需要结合最新科技成果,不断探索以提升监测仪器性能。     

果汁运输改装船关键工程控制方案研究

果汁运输船是将新鲜果汁从产地输送至需求地的主要海上远程运输工具,是解决果汁长时间存放、运输的有效载体。由于集装箱船、果汁运输船两型船舶船体结构特点类似,因此把集装船改装为果汁运输船,其改装成本远低于新造果汁运输船。文章研究集装箱船改装为果汁运输船的关键工程控制方案,探索改装技术思路,为类似改装工程提供借鉴。     

Effects of passenger characteristics and terminal layout on airport retail revenue: an agent-based simulation approach

This paper examines the effect of passenger characteristics and terminal layout on airport retail revenue using an agent-based simulation approach. Simulation results show that passenger mix (that is, the mix of shopper types according to a typology of airport shoppers) has a profound effect on airport retail revenue; the larger the number of ‘shopping lovers’ there are among passengers, the higher the airport retail revenue. Results also reveal that group travel can lead to negative effects on retail in certain terminal layouts, and that the amount of free dwell time that a passenger has can affect spending due to less retail engagement. This paper shows a combined effect of passenger characteristics and terminal layout on airport retail revenue, and discusses the implications of these results for future airport terminal design that aims to maximise retail potential.     

Exploring the issue of integrating logistics and traffic control in urban areas

This paper proposes an optimization framework for urban transportation networks’ (re-)design which explicitly takes into account the specific decision-making processes of ordinary users and logistic operators. Ordinary users are typically commuters whose travels consist of well-defined pairs of origin and destination points, while logistic operators make deliveries at multiple locations. Obviously, these two user classes have different objectives and scopes of action. These differences are seldom considered in traffic research since most models aggregate the flow demand in OD matrices and use assignment models to predict the response of all users as if the dynamics of their optimization processes were of the same nature. This work demonstrates that better results can be achieved if the particular features of each user class are included in the models. It potentially improves the estimation of the responses and allows managers to shape their control measures to address specific user needs.     

A new generalized travel cost based connectivity metric applied to Scandinavian airports

This article proposes a new, generalized travel cost based method to operationalize network accessibility provided by airports. The approach is novel as it integrates features of network topology with multiple quality aspects of scheduled air transport services into one metric. The method estimates generalized travel costs for the full set of feasible travel paths between an airport and all network destinations. Rooftop modeling accounts for schedule delay and isolates the most cost-efficient travel paths per O-D relation. Respecting the assumed arrival time preference of passengers and adjusting for destination importance, connectivity scores are derived. The method is then applied to explore changes in the global connectivity pattern of Scandinavian airports from 2004 to 2018. The results suggest distinct spatial differences throughout the network, but less pronounced in size than suggested by popularly applied connectivity measures. Findings also highlight the importance of the geographical location as a determinate of an airport’s connectivity.     

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.