Real-time optimization of ship energy efficiency based on the prediction technology of working condition

Ship energy efficiency management and control is an effective strategy to improve the marine economy and reduce CO₂ emission. The determination of the best navigation speed under different working conditions is the basis and premise for real-time improvement of ship energy efficiency. In this paper, the working condition in short distance ahead of the ship related to navigation environment factors was predicted by the method of wavelet neural network, and then the best engine speed for the optimal energy efficiency under different working conditions could be determined through the established ship energy efficiency real-time optimization model. Further, by presetting the ship engine at this optimal speed, the ship energy efficiency could be guaranteed at the optimal state when the ship arrived at the navigation environment ahead of the ship, thus achieving real-time optimization of ship energy efficiency under different navigation environment factors. Experimental studies showed that the proposed optimization model was effective in energy saving and emission reduction, which could provide theoretical guidance for optimal sailing of the ship in service. Compared to traditional setting speed navigation methods, our proposed method has more practical significance to the improvement of ship energy efficiency.     

Railway transportation and environmental efficiency in China

Railway is one of the most efficient and environmental-friendly ways to transport people and goods. High-speed railway has been developing rapidly and the railway mileage has increased by 21.18% in China during the period of 2006–2011 and thus it is interesting to evaluate whether the railway transportation has reduced the environmental impact of transport in China. In this paper, we first use a non-radial DEA under managerial disposability to measure the environmental efficiency of 30 regions in China; then we propose a panel beta regression with fixed effects to model the impact of railway transportation on environmental efficiency. The results indicate that the environmental efficiency slowly increased during 2006–2011 and it exhibits regional disparities with the eastern area having the highest environmental efficiency and the western area being the lowest one; Moreover, we also find a significant positive impact of railway transportation on higher environmental efficiency.     

Incorporating negative externalities into productivity assessments of US airports

This paper analyses the efficiency of 44 US airports for the period 2005–2009. In addition to the conventional outputs (i.e., passengers, flights and cargo), we consider three undesirable externalities of airport activities: delays, noise and local air pollution. We adopt a directional distance function approach and perform a second stage analysis to investigate potential determinants of efficiency. Our base case results with only the positive outputs show that the greater the average aircraft size serving an airport and the larger the dimensions of the airport, the higher the technical efficiency. However, our results are sensitive to the inclusion of the undesirable outputs. The implications are that the inclusion of these externalities into the calculation of efficiency may impact policy decisions.     

Improving the efficiency of repeated dynamic network loading through marginal simulation

Currently, the applicability of macroscopic Dynamic Network Loading (DNL) models for large-scale problems such as network-wide traffic management, reliability and vulnerability studies, network design, traffic flow optimization and dynamic origin–destination (OD) estimation is computationally problematic. The main reason is that these applications require a large number of DNL runs to be performed. Marginal DNL simulation, introduced in this paper, exploits the fact that the successive simulations often exhibit a large overlap. Through marginal simulation, repeated DNL simulations can be performed much faster by approximating each simulation as a variation to a base scenario. Thus, repetition of identical calculations is largely avoided. The marginal DNL algorithm that is presented, the Marginal Computation (MaC) algorithm, is based on first order kinematic wave theory. Hence, it realistically captures congestion dynamics. MaC can simulate both demand and supply variations, making it useful for a wide range of DNL applications. Case studies on different types of networks are presented to illustrate its performance.     

Joint impact of competition,ownership form and economic regulation on airport performance and pricing

The combined impact of ownership form, economic regulation and competition on airport performance is analyzed using data envelopment analysis to measure cost efficiency in the first stage and regression analysis to measure the impact of the environment in the second stage. The empirical results of an analysis of European and Australian airports over a 10 year timeframe reveal that under relatively non-competitive conditions, public airports operate less cost efficiently than fully private airports. Irrespective of ownership form, regulation is necessary to emulate competitive forces thus pushing airport management towards cost efficiency and reasonable pricing policies. Under potential regional or hub competition, economic regulation inhibits airports of any ownership form from operating and pricing efficiently. Although public and fully private airports operate equally efficiently in a competitive setting, private airports still set higher aeronautical charges. Furthermore, mixed ownership forms with a majority public holding are neither cost efficient nor low price, irrespective of the level of competition.     

Technical efficiency of automobiles – A nonparametric approach incorporating carbon dioxide emissions

We conduct an empirical analysis of the technical efficiency of cars sold 2010 in Germany. The analysis is performed using traditional data envelopment analysis (DEA) as well as directional distance functions (DDF). The approach of DDF allows incorporating the reduction of carbon dioxide emissions as an environmental goal in the efficiency analysis. A frontier separation approach is used to gain deeper insight for diesel and gasoline cars. Natural gas driven cars and sport utility vehicles are also treated as different groups. The results show that the efficiency measurement is statistically yet not economically significantly influenced by the incorporation of carbon dioxide emissions. Moreover, we find that natural gas driven cars are highly inefficient even if the reduction of emissions is accounted for in the analysis.     

舰船人-机-环系统工程研究综述

  目的  航母逃生疏散过程复杂,难以量化。  方法  针对这一问题,发展了疏散人员行为模型的多用途智能代理（MUPI）算法。基于EXODUS软件,对美国海军\     

浅谈拼版技术

制版为印前工艺的重要组成部分,其工序主要包括绘制版样、拼制版式、制版三部分。本文以东北地区印刷企业的印前现状为基本依据,介绍并比较了手工拼版和手工拼版特点。     

SCR 催化器内浓度场影响因素的仿真研究

为提高 NO x 的转化效率,研究了温度、空速、氨氮比和 NO 与 NO2的摩尔比对 SCR 催化器内浓度场的影响。试验验证了 SCR 化学反应模型,将准确的化学反应动力学参数输入到 Fire 软件并建立 SCR 催化器模型,计算分析 SCR催化器内组分浓度场的影响因素。得出以下结论：温度越高,NH3和 HCNO 的浓度越高;流体涡流为喷雾液滴蒸发和热解提供了有利条件;空速太大,NO 的转化效率会降低;当氨氮比为1时,理论上 NO x 的转化效率达到最高;当氨氮比小于1时,NO x 转化效率随氨氮比的升高而升高,但在接近1时候产生氨滑移;当氨氮比大于1时,NO x 转化效率变化不大但会产生大量氨滑移。因此最佳的氨氮比应是在保证较小的氨滑移的前提下尽可能提高 NO x 转化效率。     

新能源动力耦合方式对节能效果的影响

从不同能量源的动力耦合方式入手,并考虑到当前车辆的典型控制策略和实现方式,根据车辆假定的行驶工况,对比分析了多种方案;从系统成本、关联能量、回馈效果等多个角度进行分析,分析出最优方案;并结合系统原理,转化为相关动力源的设计参数,为车辆前期设计开发提供技术支持。