Experimental study on a model azimuthing podded propulsor in ice

The objective of this study was to investigate the performance of a model azimuthing podded propulsor in ice-covered water. Model tests were carried out with two different depths of cut into the ice (15 and 35 mm), two different ice conditions (presawn and pack ice conditions), and four different azimuthing angles. The depth of cut is the maximum penetration depth of the propeller blade into the ice block. The 0.3-m-diameter model propeller was operated in a continuous ice milling condition. Ice loads were measured by several sensors which were installed in various positions on the model. Six one-axis pancake-style load cells on the top of the model measured the global loads and two six-component dynamometers were installed on the shaft to measure the shaft loads. One six-component dynamometer was attached to the one of the propeller blades inside the hub to measure the blade loads. The pod unit and propeller performance in ice are presented. Ice-related loads, which were obtained when the blade was inside the ice block, are introduced and discussed. During the propeller–ice interaction, a blade can experience the path generated by the previous blade, which is called the shadowing effect. The effects of shadowing, depth of cut, azimuthing angle, and advance coefficient on propulsor performance are presented and discussed.     

不同外加剂对OGFC混合料路用性能的影响

OGFC为开级配沥青混合料,主要由粗集料嵌挤组成,在世界各地越来越广泛地用于铺筑路面.OGFC混合料可以增大路表面渗透性,减少噪音,增强表面摩擦力,尤其是在潮湿条件下.该文主要研究不同外加剂对OGFC路用性能的影响,其混合料分别由再生聚乙烯改性沥青(RPEB)、橡胶粉改性沥青(CRMB)和70#基质沥青+纤维与矿料拌和而成.并分别采用析漏试验、肯塔堡飞散试验、渗水试验、劈裂试验、静态模量试验,车辙试验和抗滑试验评估OGFC混合料的路用性能.结果表明:纤维和聚合物可以有效地减小OGFC离析的可能性,混合料每面击实50次能相应地提高磨耗性和其他相关的性能.改性沥青混合料的抗拉强度比(TSR)低于纤维+基质沥青混合料的抗拉强度比.     

Mixed manual/semi-automated traffic: a macroscopic analysis

The use of advanced technologies and intelligence in vehicles and infrastructure could make the current highway transportation system much more efficient. Semi-automated vehicles with the capability of automatically following a vehicle in front as long as it is in the same lane and in the vicinity of the forward looking ranging sensor are expected to be deployed in the near future. Their penetration into the current manual traffic will give rise to mixed manual/semi-automated traffic. In this paper, we analyze the fundamental flow–density curve for mixed traffic using flow–density curves for 100% manual and 100% semi-automated traffic. Assuming that semi-automated vehicles use a time headway smaller than today’s manual traffic average due to the use of sensors and actuators, we have shown using the flow–density diagram that the traffic flow rate will increase in mixed traffic. We have also shown that the flow–density curve for mixed traffic is restricted between the flow–density curves for 100% manual and 100% semi-automated traffic. We have presented in a graphical way that the presence of semi-automated vehicles in mixed traffic propagates a shock wave faster than in manual traffic. We have demonstrated that the presence of semi-automated vehicles does not change the total travel time of vehicles in mixed traffic. Though we observed that with 50% semi-automated vehicles a vehicle travels 10.6% more distance than a vehicle in manual traffic for the same time horizon and starting at approximately the same position, this increase is marginal and is within the modeling error. Lastly, we have shown that when shock waves on the highway produce stop-and-go traffic, the average delay experienced by vehicles at standstill is lower in mixed traffic than in manual traffic, while the average number of vehicles at standstill remains unchanged.     

Empirical approach for predicting the cetane number of biodiesel

The cetane number is an indicator of ignition quality and thus of fuel quality in the realm of diesel engines. It is conceptually similar to the octane number used for gasoline. Generally, a compound that has a high octane number tends to have a low cetane number and vice versa. The cetane number of a diesel fuel is related to the ignition delay time. In our work the first approach is a statistical one the accuracy of which depends upon the data obtained from various papers and literature sources, as all equations used were based on this data. During prediction using more than one equation is a good approach, as it provides the accuracy as well as the relative error. The second approach is also a statistical one, but its value depends upon the saponification number and iodine value. Therefore the accuracy of this equation may be higher, since we can collect the data for saponification numbers and iodine values from literature, without needing to calculate them. Using the saponification number and iodine value we can select an optimal biodiesel as generally a good biodiesel is selected using these three values. Thus the second approach allows us the freedom to select a biodiesel.     

Variation in the value of travel time savings and its impact on the benefits of managed lanes

This paper examines the variation in the value of travel time savings (VTTS) for travelers with a managed lane (ML) option when taking an ordinary trip versus a trip that is unusual in some way. VTTS estimates vary substantially depending on the urgency of the trip made. At the low end, the mean VTTS for a traveler who wants to make extra stops and still arrive on time is approximately 10% higher than that for an ordinary trip. At the high end, a traveler running late for an appointment shows a mean VTTS that is approximately 300% higher than that for an ordinary trip. These estimates vary widely over the population of travelers. In light of these variations, the value of an uncongested travel alternative (such as MLs) is examined and found to be greatly undervalued if using typical VTTS estimates.     

Computational methodology to predict injury risk for motor vehicle crash victims: A framework for improving Advanced Automatic Crash Notification systems

Advanced Automatic Crash Notification (AACN) systems, capable of predicting post-crash injury severity and subsequent automatic transfer of injury assessment data to emergency medical services, may significantly improve the timeliness, appropriateness, and efficacy of care provided. The estimation of injury severity based on statistical field data, as incorporated in current AACN systems, lack specificity and accuracy to identify the risk of life-threatening conditions. To enhance the existing AACN framework, the goal of the current study was to develop a computational methodology to predict risk of injury in specific body regions based on specific characteristics of the crash, occupant and vehicle. The computational technique involved multibody models of the vehicle and the occupant to simulate the case-specific occupant dynamics and subsequently predict the injury risk using established physical metrics. To demonstrate the computational-based injury prediction methodology, three frontal crash cases involving adult drivers in passenger cars were extracted from the US National Automotive Sampling System Crashworthiness Data System. The representative vehicle model, anthropometrically scaled model of the occupant and kinematic information related to the crash cases, selected at different severities, were used for the blinded verification of injury risk estimations in five different body regions. When compared to existing statistical algorithms, the current computational methodology is a significant improvement toward post-crash injury prediction specifically tailored to individual attributes of the crash. Variations in the initial posture of the driver, analyzed as a pre-crash variable, were shown to have a significant effect on the injury risk.     

Hydrodynamic loads on ice-class propellers during propeller-ice interaction

Hydrodynamic loads on a propeller blocked with simulated ice were studied using a cavitation tunnel. Comparative predictions were made using a panel method. The propeller was a model of the Canadian Coast Guard's R-class icebreake propeller, and the ice block was simulated using a solid blockage. Experimental results show the open water performance of the propeller, its performance behind a blockage, and the effects of cavitation in these conditions, as well as the loading on the simulated ice block. Panel method predictions were made of the time series propeller performance in the blocked flow. Cavitation during propellerice interaction resulted in a reduction of mean suction load on the ice block. Block load measurements indicated an increase in the oscillation about the mean value of the loads, with a variation in the phase of the loading with respect to blade position as compared with the non-cavitating results. Comparisons of panel method results with the measured block loads support the reliability of the dynamic measurements.List of symbols D propeller diameter - F block drag load - K _T thrust coefficient,T/(n ² D ⁴) - K _B block load coefficient,F/(n ² D ⁴) - K _Q torque coefficient,Q/(n ² D ⁵) - Q propeller torque - T propeller thrust - n propeller rotational speed - J propeller advance coefficientV _A/(nD) - P _A ambient pressure at propeller - P _ATM atmospheric pressure - P _V vapour pressure of water - V _A propeller advance speed - dissolved gas content - _s saturated dissolved gas content at atmospheric pressure - _o open water propeller efficiency - cavitation number, (P _A –P _V )/(0.5(nD)²) - density of water     

Improved theoretical modeling of a cyclone separator as a diesel soot particulate emission arrester

Particulate matter is considered to be the most harmful pollutant emitted into air from diesel engine exhaust, and its reduction is one of the most challenging problems in modern society. Several after-treatment retrofit programs have been proposed to control such emission, but to date, they suffer from high engineering complexity, high cost, thermal cracking, and increased back pressure, which in turn deteriorates diesel engine combustion performance. This paper proposes a solution for controlling diesel soot particulate emissions by an improved theoretical model for calculating the overall collection efficiency of a cyclone. The model considers the combined effect of collection efficiencies of both outer and inner vortices by introducing a particle distribution function to account for the non-uniform distribution of soot particles across the turbulent vortex section and by including the Cunningham correction factor for molecular slip of the particles. The cut size diameter model has also been modified and proposed by introducing the Cunningham correction factor for molecular slip of the separated soot particles under investigation. The results show good agreements with the existing theoretical and experimental studies of cyclones and diesel particulate filter flow characteristics of other applications.     

Development of a probabilistic model to optimize disseminated real‐time bus arrival information for pre‐trip passengers

In the advent of Advanced Traveler Information Systems (ATIS), the total wait time of passengers for buses may be reduced by disseminating real‐time bus arrival times for the next or series of buses to pre‐trip passengers through various media (e.g., internet, mobile phones, and personal digital assistants). A probabilistic model is desirable and developed in this study, while realistic distributions of bus and passenger arrivals are considered. The disseminated bus arrival time is optimized by minimizing the total wait time incurred by pre‐trip passengers, and its impact to the total wait time under both late and early bus arrival conditions is studied. Relations between the optimal disseminated bus arrival time and major model parameters, such as the mean and standard deviation of arrival times for buses and pre‐trip passengers, are investigated. Analytical results are presented based on Normal and Lognormal distributions of bus arrivals and Gumbel distribution of pre‐trip passenger arrivals at a designated stop. The developed methodology can be practically applied to any arrival distributions of buses and passengers.