两种直接波浪能转换系统性能的比较:阿基米德波浪摆和波能浮筒(英文)

Many wave energy conversion devices have not been well received. The main reasons are that they are too complicated and not economical. However, in the last two decades direct conversion systems have drawn the attention of researchers to their widely distributed energy source due to their simple structure and low cost. The most well-known direct conversion systems presently in use include the Archimedes Wave Swing (AWS) and Power Buoy (PB). In this paper, these two systems were simulated in the same conditions and their behaviors were studied in different wave conditions. In order to verify the simulations, results of the generator of the finite element computations were followed. An attempt was made to determine the merits and drawbacks of each method under different wave conditions by comparing the performance of the two systems. The wave conditions suitable for each system were specified.     

军船雷达目标有效截面预报和缩减研究(英文)

Radar cross section(RCS) is the measurement of the reflective strength of a target.Reducing the RCS of a naval ship enables its late detection,which is useful for capitalizing on elements of surprise and initiative.Thus,the RCS of a naval ship has become a very important design factor for achieving surprise,initiative,and survivability.Consequently,accurate RCS determination and RCS reduction are of extreme importance for a naval ship.The purpose of this paper is to provide an understanding of the theoretical background and engineering approach to deal with RCS prediction and reduction for naval ships.The importance of RCS,radar fundamentals,RCS basics,RCS prediction methods,and RCS reduction methods for naval ships is also discussed.     

The changing accuracy of traffic forecasts

Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy—traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time: more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.

     

A multi-objective train scheduling model and solution

This paper develops a multi-objective optimization model for the passenger train-scheduling problem on a railroad network which includes single and multiple tracks, as well as multiple platforms with different train capacities. In this study, lowering the fuel consumption cost is the measure of satisfaction of the railway company and shortening the total passenger-time is being regarded as the passenger satisfaction criterion. The solution of the problem consists of two steps. First the Pareto frontier is determined using the -constraint method, and second, based on the obtained Pareto frontier detailed multi-objective optimization is performed using the distance-based method with three types of distances. Numerical examples are given to illustrate the model and solution methodology.     

Micro-simulation modelling for traffic safety: A review and potential application to heterogeneous traffic environment

This paper critically reviews micro-simulation modelling applications for traffic safety evaluation with respect to the use of different simulation tools, the application of surrogate safety indicators under different aspects of road environments and crash considerations. General input variables used to develop the models; key parameters for crash prediction; and calibration and validation approaches are explored in the paper. The strengths and weaknesses of used simulation packages for traffic safety evaluation are also pointed out. Moreover, recent advancements in the development and application of traffic safety micro-simulation model for safety assessment are also discussed.Despite having a number of studies, there is still a significant void in the development and application of simulation model to evaluate traffic safety of non-lane based heterogeneous traffic environments that predominate in many developing countries. The paper assessed the potential application of traffic safety micro-simulation model in heterogeneous traffic environments. Finally, a number of potentially fruitful future research directions are highlighted.     

An exploration of shoppers travel mode choice in visiting convenience stores in the UK

Using data from over 2000 convenience store customers within and outside London, this paper explores how individuals access their convenience stores and how significant the influence of their socio-demographics, shopping types and trip chaining is to their mode choice in visiting the stores. Trip chaining is found to be crucial in influencing customers' mode choice and their visit frequency. The application of logit models also shows that frequent shoppers are the ones most likely to visit the stores on foot. Interestingly, the estimation results also show that the location's density, shopping types and the day of the week are not significant in influencing travel modes. Customers who live in the most deprived areas are less likely to use a private car in visiting the stores.