Exergetic analysis of fuel cell micropowerplants fed by methanol

In the present study, a hydrogen polymer electrolyte fuel cell (PEFC) micropowerplant in combination with a steam reformer fed by methanol and a direct methanol fuel cell (DMFC) micropowerplant are analyzed numerically regarding their exergetic efficiency. The effects of concentration and activation overpotentials, and ohmic resistance on the efficiency are considered in quasi-two-dimensional fuel cell models. The influence of significant operational parameters on the exergetic efficiency is examined numerically. Experimental results are conducted for the steam reformer. This work shows the importance of an exergy analysis of the fuel cell as part of an entire thermodynamic system generating electric power and compares PEFC and DMFC micropowerplants exergetically.     

Improved performance of deep-blue polymer light-emitting diodes by one-step coating self-assembly hole injection/transport nanocomposites with both the optical and electrical optimization

In this study we demonstrate an easy solution-processed highly efficient deep-blue polymer light-emitting diode (PLED) via a simple one-step coating of self-assembly hole injection/transport nanocomposites to achieve both a finer hole ohmic contact and an increased light outcoupling, which is the first time report about both the optical and electrical optimization without necessitating changes in the design or structure of the wide bandgap deep-blue PLEDs themselves. The contact angle and surface energy measurement results demonstrate that triazine-based hole injection molecules can vertically migrate towards the bottom PEDOT:PSS layer to obtain a stable minimum of free energy, resulting in an optimal top-to-bottom HOMO energy level arrangement and an improved hole mobility in deep-blue PLEDs. The random surface nanostructure was formed on top of the hole bilayer, leading to the enhancement of light outcoupling verified by transmittance, transmittance haze and light extraction efficiency. Furthermore, in order to explore the reasons of the hole light scattering formation process, a transient drying monitoring technique is applied to track the drying process of the nanostructure films, revealing this approach effectiveness by easily modifying mixing ratios for obtaining different light outcoupling abilities.     

基于轨迹数据的出租车充电站选址方法

针对目前电动汽车充电桩利用率低、充电站盈利困难的问题,提出了一种基于轨迹数据的出租车充电站选址方法。分析了出租车停留状态的轨迹数据特性,提取可支持车辆充电时长的出租车停留点。对停留点进行地图匹配,筛选掉在道路上的停留点。对非道路区域停留点进行聚类,得出多辆车停留密集区域作为充电站地点区域。分析了停留点的时间分布,以充电站区域停留点高峰时候的停留点数为参考对充电站定容。以福州市4?416辆出租车的轨迹数据为实验样本得出了16个充电站的选址方案,以司机的充电便利性与充电站的经济性进行合理性分析。结果表明：在选出的充电站中涉及了2?741辆车,可为六成以上的出租车提供非运营状态下充电,折旧期（六年）内充电站总盈利为4?316.56万元。可见,该方法既能为车主提供充电便利,又可有效保证充电站的盈利,可为电动出租车充电站建设与运营提供有效参考。     

Wavelet based medical image super resolution using cross connected residual-in-dense grouped convolutional neural network

In clinical analysis and diagnosis, high resolution (HR) computed tomography (CT) images are required for proper treatment of a patient. Developing HR medical images by X-ray CT devices require extended radiation exposure with large radiative dosages, putting the patient at potential risk of inducing cancer. So, radiation exposure should be reduced. However, photon starvation and beam hardening in low-dose X-rays will cause severe artifacts. Thus, an accurate reconstruction of low-dose X-ray CT images is required. To this end, we propose a wavelet based multi-channel and multi-scale cross connected residual-in-dense grouped convolutional neural network (WCRDGCNN) for accurate super resolution (SR) of medical images. The adopted filter groups reduce the connection weights, thereby reducing the computational complexity. Gradient vanishing problem is tackled by using residual and dense skip connections. The extensive experimentation results on benchmark datasets show that our method outperforms the state-of-the-art SR methods.     

A fully explicit method for incompressible flow computation

A new formulation of the Navier–Stokes equations is introduced to solve incompressible flow problems. It keeps the benefits of the penalty method, that is, velocity and pressure can be obtained separately and no pressure-Poisson equation is involved. Unlike the penalty method the formulation is more stable or less stiff and then explicit time integration can be applied for easy implementation. No linear or nonlinear system need be solved in the method. In the case that a large number of time steps are needed a parallelization based on domain decomposition is applied to reduce the computational time. With the explicit time integration the parallel implementation and its message passing are very simple as well.     

Thermal conductivity and tensile response of defective graphene: A molecular dynamics study

In this study, effects of point vacancy, Stone–Wales and bivacancy defects on thermal conductivity and tensile response of single-layer graphene sheets are studied using classical molecular dynamics (MD) simulations. Using non-equilibrium molecular dynamics (NEMD) method, we found that thermal conductivity of graphene is considerably sensitive to existence of defects. It was observed that only 0.25% concentration of defects in graphene lead to significant reduction of graphene thermal conductivity by around 50%. By applying uniaxial tensile loading, we studied the deformation process of graphene. We found that elastic modulus, tensile strength and strain at failure of graphene decrease by increase of defects concentrations. Obtained results suggest that thermal conduction in graphene is much more vulnerable to defects in comparison with mechanical properties. Reported results by this work provide an overall viewpoint concerning the intensity of defects’ effects on the graphene thermal and mechanical response.     

Squarylium and rubrene based filterless narrowband photodetectors for an all-organic two-channel visible light communication system

In this paper, based on 1,3-bis[(3,3-dimethylindolin-2-ylidene)methyl]squaraine (ISQ), which has narrowband red-light absorption, and Rubrene, which possesses significant blue-light absorption, two color-selective organic photodetectors (OPDs) are developed. By quantum chemistry calculation, the mechanism of ISQ's sharp absorption spectrum is analyzed. Without input filtering, the two OPDs are well suited for two-channel visible light communications (VLC) system due to their good orthogonality of response spectrum and exceptional features, such as flexibility and ability to realize large-area thin-film manufacturing. With the two OPD as receivers and corresponding organic light emitting diodes (OLEDs) as data transmitters respectively, a two-channel VLC system delivering a bit-rate of 530 kb/s in the blue-light channel and 180 kb/s in the red-light channel was experimentally demonstrated. The two channels have good orthogonality when they operate together. This all-organic VLC system demonstrates the feasibility and benefit for the application of organic electronics in the communication field.     

Web service reliability prediction based on machine learning

Web service reliability is an important mission that keeps web services running normally. Within web service, the web services invoked by users not only depend on the service itself, but also on web load condition (such as latency). Due to the features of web dynamics, traditional reliability methods have become inappropriate; at the same time, the web condition parameter sparsity problem will cause inaccurate reliability prediction. To address these new challenges, in this paper, we propose a new web service reliability prediction method based on machine learning considering user, web service and web condition. First we solve the web condition parameter sparsity problem, then we use the k-means clustering method to aggregate past invocation data, incorporate user, service, and web condition parameters to build a reliability feedback matrix, at last we predict web service reliability by considering specific web condition environments. The experiment shows that our machine learning method is able to solve the data sparsity problem and improve accurate web service reliability prediction, and we discuss how data sparsity and the number of feedback clusters to affect web service reliability prediction.     

牵引电缆金属护层的雷击感应电压

基于牵引电缆结构分析了电缆金属护层感应电压产生机理,探讨了雷电流对于金属护层对地电压的影响。在此基础上,利用电磁暂态仿真软件构建了牵引供电系统、牵引电缆以及雷电流模型,仿真分析了AT供电方式下避雷器接地和牵引电缆接地对雷击感应电压的影响。结果表明,当避雷器的接地电阻小于5Ω并且电缆在靠近接触网一端安装护层保护器时,电缆金属护层的雷击感应电压低于外护套冲击耐受电压。     

Modeling and online parameter estimation of intake manifold in gasoline engines using sliding mode observer

Model based control of automotive engines for fuel economy and pollution minimization depends on accuracy of models used. A number of mathematical models of automotive engine processes are available for this purpose but critical model parameters are difficult to obtain and generalize. This paper presents a novel method of online estimation of discharge coefficient of throttle body at the intake manifold of gasoline engines. The discharge coefficient is taken to be a varying parameter. Air mass flow across the throttle body is a critical variable in maintaining a closer to stoichiometric air fuel ratio; which is necessary to minimize the pollution contents in exhaust gases. The estimation method is based on sliding mode technique. A classical first Sliding mode observer is designed to estimate intake manifold pressure and the model uncertainty arising from the uncertain and time varying discharge coefficient is compensated by the discontinuity/switching signal of sliding mode observer. This discontinuity is used to compute coefficient of discharge as a time varying signal. The discharge coefficient is used to tune/correct the intake manifold model to engine measurements. The resulting model shows a very good agreement with engine measurements in steady as well s transient state. The stability of the observer is shown by Lyapunov direct method and the validity of the online estimation is successfully demonstrated by experimental results. OBD-II (On Board Diagnostic revision II) based sensor data acquisition from the ECU (Electronic Control Unit) of a production model vehicle is used. The devised algorithm is simple enough to be designed and implemented in a production environment. The online estimation of parameter can also be used for engine fault diagnosis work.