A porous cell method for the simulation of fluid-solid interactions

There are many ways of describing a solid,porous or fluid region of the computational domain when solving the Navier-Stokes equations(NSE)for flow motions.Amongst these the porous cell method is one of the most flexible approaches.In this method,a parameter is defined as a ratio of the volume open to water and air in a calculation cell to its cell volume.In the calculation,the same numerical procedure is applied to every cell and no explicit boundary conditions are needed at solid boundaries.The method is used to simulate flow through porous media,around solid bodies and over a moving seabed.The results compare well with experimental data and other numerical results.In our future work the porous cell method will be applied to more complex fluid-solid interaction situations.     

柔性路面车辙预估的粘弹性方法

沥青混合料的粘弹性流动导致沥青路面产生永久变形(车辙)。对于粘弹性体系,永久变形与材料的弹性参数无关,但可通过采用粘性参数的线弹性模型预估出来。为了确定沥青混合料在较大环境变化条件下的粘性,该文引入了一个新的基于常规试验数据的简单理论方法,并将根据此方法得到的车辙预估深度与法国新近的一个足尺试验数据进行对比,结果表明此线性车辙模型的适用性较好。     

The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework

Incorporation of externalities in the Multi-Objective Network Design Problem (MO NDP) as objectives is an important step in designing sustainable networks. In this research the problem is defined as a bi-level optimization problem in which minimizing externalities are the objectives and link types which are associated with certain link characteristics are the discrete decision variables. Two distinct solution approaches for this multi-objective optimization problem are compared. The first heuristic is the non-dominated sorting genetic algorithm II (NSGA-II) and the second heuristic is the dominance based multi objective simulated annealing (DBMO-SA). Both heuristics have been applied on a small hypothetical test network as well as a realistic case of the city of Almelo in the Netherlands. The results show that both heuristics are capable of solving the MO NDP. However, the NSGA-II outperforms DBMO-SA, because it is more efficient in finding more non-dominated optimal solutions within the same computation time and maximum number of assessed solutions.     

SUPPRESSION OF GROWTH OF A HUMAN LIVER－DERIVED CELL LINE BY ENDOGENOUSLY PRODUCED PARATHYROID HORMONE－RELATED PEPTIDE

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Influence of oxygenate content on particulate matter emission in gasoline direct injection engine

The relationship between the oxygen content in gasoline and the particulate emission (particle number and weight) was investigated. In order to study the influence of the engine configuration on the particulate emission, four vehicles were tested in which the following systems were installed: Vehicle 1 was equipped with direct injection system which uses central mounted outwardly opening injectors. Vehicle 2 and 3 used direct injection with a side mounted multihole injectors and Vehicle 4 had port fuel injection system. Methyl tert-butyl ether (MTBE) was used as the oxygen booster. The oxygen content in the gasoline was varied from 1 to 3 wt%, which corresponds with an MTBE dosage from 3.55% to 16.11%. This study used fuel that contained the same octane number with a 2% oxygen content without oxygen components, and it was used as the reference fuel in order to distinguish the effect of the oxygen content increases and the octane boosts that result from the MTBE. All vehicle tests were performed on a roller type chassis dynamometer using the New European Driving Cycle (NEDC) and Federal Test Procedure-75 (FTP-75) cycle. The experiment results demonstrate that the oxygen content increases in the gasoline reduced the particulate emission in vehicles with direct injection engines. An equivalent phenomenon was observed in a vehicle with a port fuel injection engine, but its absolute particle number was much smaller than that of the gasoline direct injection engine. The amount of reduction of the particle number in the start (cold) phase of the test cycle was significant compared with the later (hot) phase engine operation. However, particulates were emitted even though the engine was fully warmed up, especially when the engine was highly loaded. Other factors such as fuel economy or other exhaust emissions were not significantly affected by the oxygen content.     

In-vehicle display HMI safety evaluation using a driving simulator

Recently, telematics services and in-vehicle display devices such as the CNS (Car Navigation System) have become new causes of traffic accidents. These accidents are caused by ‘Inattention’ from the increase of the driver’s mental workload while he/she is driving. The driver of a vehicle (except for emergency or police vehicles) must not use a hand-held mobile phone while the vehicle is moving. To address this problem, Australia, England, Italy, Brazil and some states in the US have banned the use of hand-held mobile devices during driving. However, there are no restrictions on the use of in-vehicle displays or on the display’s positions. The position of a navigation system in a vehicle should be assessed objectively, and the effect of the position on the driver’s attention should be studied. Some existing research reports that in-vehicle distraction not only leads to reduced speeds and more frequent lane switching, but also more gazing by the driver to the centre of the road. In this study, to develop an assessment method and to propose the proper position of a CNS, an experiment is carried out in a driving simulator environment. Different methods to track the gaze and physical parameters of the driver are used for HMI (Human-Machine Interface) assessment. The experiment is carried out in a driving simulator to observe the glancing distribution during driving according to the position of the navigation system. Fourteen subjects participated in this experiment. Changes in subjects’ physiological signals and glancing distribution rates were collected.     

Predicting auto-ignition characteristics of RCCI combustion using a multi-zone model

The objective of new combustion concepts is to meet emission standards by improving fuel air mixing prior to ignition. Since there is no overlap between injection and ignition, combustion is governed mainly by chemical kinetics and it is challenging to control the phasing of ignition. Reactivity Controlled Compression Ignition (RCCI) combustion aims to control combustion phasing by altering the fuel ratios of the high- and low octane fuel and injection timings. In this study the dual fuel blend is prepared with gasoline and diesel fuels. The applied injection timings of the diesel are very early (90 to 60° CA bTDC). In the detailed reaction mechanism, n-heptane and iso-octane represent diesel and gasoline fuel, respectively. A multi-zone model approach is implemented to perform RCCI combustion simulation. Ignition characteristics are analyzed by using CA50 as the main parameter. In the experiments for the early direct injection (DI) timing advancing the injection time results in a later ignition. Qualitatively, the trend effect of the diesel injection timing and the effect of the ratio gasoline/diesel are captured accurately by the multi-zone model.     

Three-speed transmission system for purely electric vehicles

This paper discusses the necessity of using a transmission system to improve the energy efficiency of purely electric vehicles (EVs). The energy efficiency of an electric motor varies at different operating points to meet the output power demand. The three gear ratios of a transmission system can maintain the motor speed within a stable region with relatively high energy efficiency, while various vehicle speeds are needed. This work is based on a light EV prototype. The optimized gear ratios of this transmission result in a considerably reduced energy consumption of 9.3% compared with conventional EVs with single-speed reducers under the condition of the Urban Dynamometer Driving Schedule driving cycle. Thus, the transmission system is necessary to improve the energy efficiency of EVs.     

Real-time vision-based blind spot warning system: Experiments with motorcycles in daytime/nighttime conditions

This paper describes a real-time vision-based blind spot warning system that has been specially designed for motorcycles detection in both daytime and nighttime conditions. Motorcycles are fast moving and small vehicles that frequently remain unseen to other drivers, mainly in the blind-spot area. In fact, although in recent years the number of fatal accidents has decreased overall, motorcycle accidents have increased by 20%. The risks are primarily linked to the inner characteristics of this mode of travel: motorcycles are fast moving vehicles, light, unstable and fragile. These features make the motorcycle detection problem a difficult but challenging task to be solved from the computer vision point of view. In this paper we present a daytime and nighttime vision-based motorcycle and car detection system in the blind spot area using a single camera installed on the side mirror. On the one hand, daytime vehicle detection is carried out using optical flow features and Support Vector Machine-based (SVM) classification. On the other hand, nighttime vehicle detection is based on head lights detection. The proposed system warns the driver about the presence of vehicles in the blind area, including information about the position and the type of vehicle. Extensive experiments have been carried out in 172 minutes of sequences recorded in real traffic scenarios in both daytime and nighttime conditions, in the context of the Valencia MotoGP Grand Prix 2009.