Numerical simulation of water and heat transport in the cathode channel of a PEM fuel cell

Cathode channel of a PEM fuel cell is the critical domain for the transport of water and heat. In this study, a mathematical model of water and heat transport in the cathode channel is established by considering two-phase flow of water and air as well as the phase change between water and vapor. The transport process of the species of air is governed by the convection-diffusion equation. The VOSET (coupled volume-of-fluid and level set method) method is used to track the interface between air and water, and the phase equilibrium method of water and vapor is employed to calculate the mass transfer rate on the two-phase interface. The present model is validated against the results in the literature, then applied to investigate the characteristics of two-phase flow and heat transfer in the cathode channel. The results indicate that in the inlet section, water droplets experience three evolution stages: the growing stage, the coalescence stage and the generation stage of dispersed water drops. However, in the middle and outlet sections of the channel, there are only two stages: the growth of water droplets, and the formation of a water film. The mass transfer rate of phase change in the inlet section of the channel varies over time, exhibiting an initial increase, a decrease followed, and a stabilization finally, with the maximum and stable values of 1.78 × 10^?4 kg/s and 1.52 × 10^?4 kg/s for Part 1, respectively. In the middle and outlet sections, the mass transfer rate increase firstly and then keeps stable gradually. Furthermore, regarding the distribution of the temperature and vapor mass fraction in the channel, near the upper surface of the channel, the temperature and vapor mass fraction first change slightly (x < 0.03 m) and then rapidly decrease with fluctuations (x > 0.03 m). In the middle of the channel, the temperature and vapor mass fraction slowly decrease with fluctuation.     

A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model

Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. We use a newly developed software package, a Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), to evaluate the effectiveness and efficiency of ten widely used SA methods, including seven qualitative and three quantitative ones. All SA methods are tested using a variety of sampling techniques to screen out the most sensitive (i.e., important) parameters from the insensitive ones. The Sacramento Soil Moisture Accounting (SAC-SMA) model, which has thirteen tunable parameters, is used for illustration. The South Branch Potomac River basin near Springfield, West Virginia in the U.S. is chosen as the study area. The key findings from this study are: (1) For qualitative SA methods, Correlation Analysis (CA), Regression Analysis (RA), and Gaussian Process (GP) screening methods are shown to be not effective in this example. Morris One-At-a-Time (MOAT) screening is the most efficient, needing only 280 samples to identify the most important parameters, but it is the least robust method. Multivariate Adaptive Regression Splines (MARS), Delta Test (DT) and Sum-Of-Trees (SOT) screening methods need about 400–600 samples for the same purpose. Monte Carlo (MC), Orthogonal Array (OA) and Orthogonal Array based Latin Hypercube (OALH) are appropriate sampling techniques for them; (2) For quantitative SA methods, at least 2777 samples are needed for Fourier Amplitude Sensitivity Test (FAST) to identity parameter main effect. McKay method needs about 360 samples to evaluate the main effect, more than 1000 samples to assess the two-way interaction effect. OALH and LP_τ (LPTAU) sampling techniques are more appropriate for McKay method. For the Sobol' method, the minimum samples needed are 1050 to compute the first-order and total sensitivity indices correctly. These comparisons show that qualitative SA methods are more efficient but less accurate and robust than quantitative ones.     

基于纹理切换的虚拟战斗人员三维显示方法

为了解决形象化模型显示方法硬件依赖性过高、不易实现推广等问题,从“分队指挥模拟对抗演练系统”虚拟战斗人员显示的实际需要出发,提出了一种基于纹理切换的虚拟战斗人员三维显示方法. 重点叙述了这种纹理切换显示方法的基本思路、算法思想、技术路线以及具体实现;并且对实现过程中涉及到的在视点角度发生变化的条件下,如何同时保持纹理框架朝向不变以及如何保持虚拟战斗人员逻辑方向不变两个纹理切换的关键问题进行了重点研究.     

与抽样相结合的县级作物遥感面积估算应用实例

为了探索遥感卫星影像和无人机调查在实际遥感面积估算中的调查效果和适用性,以广东省阳春市晚稻为例,采用卫星影像与无人机调查结果相结合,使用两种面积估算方法进行2013年晚稻种植面积估算。实验结果表明,比估计和回归估计方法的估算结果分别为22 501.1hm2和22 781.1hm2,二者的CV分别为8.84%和1.03%。研究结果表明:1无人机调查可获得高质量的面积测量信息;2优化后的样本能够支持面积估算过程,但其理论意义需要更进一步地讨论与证明;3卫星数据与无人机调查数据相结合的方法可以提供满足统计精度要求的面积测量结果,具有良好的应用前景。     

基于ArcObject和GM(1,1)的海岸线预测系统

海岸线变化对海岸带地区的可持续发展有重要的影响作用。该文以 Microsoft C#.NET为软件平台,应用ESRI公司提供的组建对象模型对象库——ArcObjects,利用GM(1,1)模型,通过设置预测原点和侧线,并与海岸线矢量数据进行叠加,得到若干GM(1,1)原始数列,由此计算出海岸线变化的预测点,实现了对海岸线变化的趋势预测,并将该预测系统应用于辽宁省国土资源规划地理信息系统中。     

A Copula based observation network design approach

In this paper, a method for environmental observation network design using the framework of spatial modeling with copulas is proposed. The methodology is developed to enlarge or redesign an existing monitoring network by taking the configuration which would increase the expected gain defined in a utility function. The utility function takes the estimation uncertainty, critical threshold value and gain-loss of a certain decision into account. In this approach, the studied spatial variable is considered as a random field in where variations in time is neglected and the variable of interest is static in nature. The uniqueness of this approach lies in the fact that the uncertainty estimation at the unsampled location is based on the full conditional distribution calculated as conditional copula in this study. Unlike the traditional Kriging variance which is a function of mere measurements density and spatial configuration of data points, the conditional copula account for the influence from data values. This is important specially if we are interested in purpose oriented network design (pond) as for example the detection of noncompliance with water quality standards, the detection of higher quantiles in the marginal probability distributions at ungauged locations, the presence or absence of a geophysical variable as soil contaminants, hydrocarbons, golds and so on. An application of the methodology to the groundwater quality parameters in the South-West region of Germany shows its potential.     

Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling

Land surface and climate modelling requires continuous and consistent Leaf Area Index (LAI). High spatiotemporal resolution and long-time record data are more in demand nowadays and will continue to be in the future. MODIS LAI products meet these requirements to some degree. However, due to the presence of cloud and seasonal snow cover, the instrument problems and the uncertainties of retrieval algorithm, the current MODIS LAI products are spatially and temporally discontinuous and inconsistent, which limits their application in land surface and climate modelling. To improve the MODIS LAI products on a global scale, we considered the characteristics of the MODIS LAI data and made the best use of quality control (QC) information, and developed an integrated two-step method to derive the improved MODIS LAI products effectively and efficiently on a global scale. First, we used the modified temporal spatial filter (mTSF) method taking advantage of background values and QC information at each pixel to do a simple data assimilation for relatively low quality data. Then we applied the post processing-TIMESAT (A software package to analyze time-series of satellite sensor data) Savitzky-Golay (SG) filter to get the final result. We implemented the method to 10 years of the MODIS Collection 5 LAI data. In comparison with the LAI reference maps and the MODIS LAI data, our results showed that the improved MODIS LAI data are closer to the LAI reference maps in magnitude and also more continuous and consistent in both time-series and spatial domains. In addition, simple statistics were used to evaluate the differences between the MODIS LAI and the improved MODIS LAI.     

Development and application of a simulation model for changes in land-use patterns under drought scenarios

In arid and semiarid areas of northern China, one of the most vulnerable regional environments, water resources are a key constraint on socioeconomic development. We constructed a simulation model for land-use patterns under a drought transition (i.e., the increased frequency and duration of drought since the late 1970s in the Yongding River Basin study area) to account for the complexity of both the driving factors behind land-use change and the micro-level changes in land-use patterns. This model was a combination of the “top-down” system dynamics model, the “bottom-up” cellular automaton model, and the artificial neural network model. In this model, we considered the socioeconomic development and water resource restrictions, as well as the balance between the land-use requirements and the land supply. We then verified the model through a case study. The results demonstrated the value of constructing a simulation model driven by water resource constraints under the influence of drought. The spatial distribution of land uses in future scenarios will help support decision-making for sustainable regional development.     

公路弃土场坡面产流特征及过程模拟

公路弃土场坡面径流的模拟对流域水资源评价和道路侵蚀模型的构建均具有重要意义。通过不同雨强(0.6～2.79mm/min)的人工降雨试验,对不同坡度(19.4%～78.1%)弃土场坡面及坡度为30.6%的弃土场施工道路的坡面径流过程进行了研究。结果表明:在小雨强下(0.6mm/min)径流显著受到土壤干容重及小区坡度的影响,而随雨强的增加,坡度及土壤干容重对径流的影响逐渐被降雨所覆盖。使用Green-Ampt入渗模型可以较为准确地计算公路弃土场坡面径流,模型有效系数达0.975。     

利用NDVI时间序列识别汶川地震滑坡的分布

利用MODIS NDVI产品,生成了全年16天间隔的NDVI时间序列,再经过Savitzky-Golay滤波后消除了云的影响,可以用来识别滑坡。假设2007年、2008年研究区土地利用状况基本不变,对比2007年和2008年两年的NDVI序列,并结合汶川地震的发生时间,可以识别出研究区发生滑坡的区域分布。结合平武县30mETM目视解译滑坡结果,对自动识别方法进行了验证。结果表明:MODIS识别出的滑坡与目视解译结果匹配较好。在此基础上,将本文方法应用到受汶川地震影响最严重的13个县区级行政区,并综合研究区坡度信息,识别出了汶川重灾区滑坡分布概图。