航空电磁发射线圈自感系数的精确计算

基于Maxwell计算螺线管电感量的方法,这里给出了适于编程计算单匝回线及多匝多层同轴空心线圈自感系数的的算法。根据航空电磁发射线圈的特点构造了几个模型,用以验证该计算方法的正确性,并表明了本文提供的算法和程序,可以为航空电磁线圈的优化设计提供理论和数据支持。     

教育测量数据的多元自建模模型分析

将关于形状不变的自建模回归模型推广到多元自变量,解决了计算问题,并结合教育测量数据给出了实例。该模型既可以反映多条曲线走势的共性,又可以反映每条曲线之间的相互关系及其个性。     

Point Cumulative Semivariogram for Identification of Heterogeneities in Regional Seismicity of Turkey

Geological events are neither isotropic nor homogeneous in their occurrences. These two properties present difficulties for spatial modeling of regionalized variables. This paper presents a point cumulative semivariogram (PCSV) technique for quantifying the heterogeneity characteristics of the phenomenon concerned. The basis of the methodology is to obtain experimental PCSVs for each measurement point which led to estimation of radius of influence around each site. In addition, the experimental PCSVs provide basic information about the heterogeneity of the geological variable in the region, and furthermore many useful interpretations can be made concerning the regional variability of the variable. It provides the measure of cumulative similarity of a regional variable around any measurement site. Because PCSV is a means of measuring total similarity, maps at fixed similarity levels are provided in order to document the regional heterogeneity. Identification of heterogeneities depends on the comparison of fixed PCSV values at a multitude of irregularly scattered sites. The PCSV methodology has been applied to the regional seismic data of Turkey.     

Unsteadiness as a cause of non-equality of eddy diffusivities for heat and vapour at the base of an advective inversion

This paper examines the effect of non-stationarity of the wind on similarity of the eddy diffusivities for heat and vapour within a stable layer at the bottom of an internal boundary layer formed downwind of a dry-to-wet transition. First, we present some experimental data taken above a rice crop downwind of very extensive dry range lands at Warrawidgee, NSW, Australia. These data establish that periods of higher wind speed were associated with periods of higher saturation deficit in the canopy of the rice crop, and lower Bowen ratio. It is shown that Bowen ratios calculated for 30-second sub-intervals varied three-fold within a single 20-minute averaging period. Thus periods of higher wind speed corresponded to periods of higher moisture flux and smaller sensible heat flux.An idealized situation is then analysed theoretically. It is assumed that the time scale of the slow variations of the wind is long compared with the surface-layer time scale and that fetch is sufficient that the air near the ground is in continuous equilibrium with the surface. Using a two-scale Reynolds decomposition of the fluctuating wind and scalar variables into active and inactive components, it is shown that unsteadiness can lead to an eddy diffusivity for saturation deficit, calculated as the ratio of average flux to average gradient, that is larger than that for total energy calculated in a similar way. Using this ratio to calculate the ratio of diffusivities for temperature and humidity, K_T/K_q, it is found that the latter can be much larger than one if the Bowen ratio is small and negative. Despite this, assuming K_T = K_q and using the Bowen ratio method to calculate surface energy fluxes will usually incur only minor errors.     

包含局地自由对流的Monin—Obukhov相似性函数

本文从湍流产生和发展的本质出发,以湍流动能和湍流混合长为湍流输送的决定因子,用因次分析的方法得到了一套可包括局地自由对流在内的不稳定大气近地层Monin－Obukhov相似性函数。这套相似性函数不仅有较充分的理论依据,而且还有较明确的物理含意。它能在极端情况下自动蜕化出局地自由对流相似性预测形式。     

Application of integrated back‐propagation network and self organizing map for flood forecasting

Much of the nonlinearity and uncertainty regarding the flood process is because hydrologic data required for estimation are often tremendously difficult to obtain. This study employed a back‐propagation network (BPN) as the main structure in flood forecasting to learn and to demonstrate the sophisticated nonlinear mapping relationship. However, a deterministic BPN model implies high uncertainty and poor consistency for verification work even when the learning performance is satisfactory for flood forecasting. Therefore, a novel procedure was proposed in this investigation which integrates linear transfer function (LTF) and self‐organizing map (SOM) to efficiently determine the intervals of weights and biases of a flood forecasting neural network to avoid the above problems. A SOM network with classification ability was applied to the solutions and parameters of the BPN model in the learning stage, to classify the network parameter rules and to obtain the winning parameters. The outcomes from the previous stage were then used as the ranges of the parameters in the recall stage. Finally, a case study was carried out in Wu‐Shi basin to demonstrate the effectiveness of the proposal. Copyright © 2009 John Wiley & Sons, Ltd.     

Multifractal analysis as a tool for validating a rainfall model

A multifractal analysis was carried out in order to validate the simulation of hourly rainfall records of a local climate model for the Iberian Peninsula. Observed and simulated hourly rainfall data from four locations in Andalusia (southern Spain) were used to carry out the study. In order to detect the influence of the length of the data series on the results, two different sizes were used for the real data: 4 years, and 20 years. The results show that algebraic tails are required to fit the probability distribution of extreme rain event sizes, and rain and dry event durations for both kinds of rainfall data. Similar results are found for the extreme rain event sizes and dry event durations fits when the real and synthetic data are considered. Nevertheless, some differences appear in the cases of rain event durations. The detection of the presence of a first‐order multifractal phase transition associated with a critical moment in the empirical moment scaling exponent function and the results of the extreme rain event sizes fits, reveal that real rainfall is a self‐organized criticality (SOC) process. That behaviour is less evident in the simulated rainfall series. The same ‘synoptic maximum’ value was found for each place with both types of rainfall data. A time clustering analysis was carried out applying the count‐based periodogram and the Fano factor methods. Some periodicities have been detected in the periodograms, especially for the longest real rainfall data series. Copyright © 2007 John Wiley & Sons, Ltd.     

GRACE时变重力数据后处理方法评价

针对GRACE Level2卫星时变重力数据后处理方法如何评价的问题,该文以中国数字地震观测网络获得的青藏高原地区地面重力变化图像为参考,基于平均结构相似性等图像相似度指标,研究了与该区域地面重力观测同期、不同后处理方法得到的GRACE卫星重力变化图像的可靠性。结果显示,GRACE卫星重力和地面重力观测结果具有一定的可比性,滑动窗口去相关滤波和高斯400 km滤波的组合方法可以获得最优的处理效果。本文的方法和结论对GRACE及GRACE Follow-On卫星重力数据应用中后处理方法和参数的选取有一定的借鉴意义。     

气象无线传感网观测节点的设计与实现

针对传统自动气象站对电力和通讯基础设施依赖性强,应用环境受到限制的问题,设计并实现了一种基于无线传感器网络的气象观测节点。气象观测节点的硬件系统以CC2530芯片为核心,使用锂电池供电,通过模拟和数字接口连接气象传感器,射频部分工作在2.4 GHz。软件系统以TinyOS操作系统为基础,开发了基于LEPS协议的多跳路由协议和气象传感器驱动程序。在野外环境中对气象观测节点的功耗、通信距离、传感器及组网性能进行了测试。测试结果表明,气象观测节点在没有电力和通信基础设施的环境中能够形成一个稳定的多跳自组织数据采集与传输网络,适合在高山、海岛、沙漠等艰苦地区进行部署和应用。     

基于FastICA算法和MODIS数据的水稻面积提取

以苏、皖、赣三省为研究区域,采用FastICA算法从MODIS数据中提取2010年水稻种植面积,并验证该算法在混合像元分解中的有效性。在对2010年46景8 d合成地表反射率产品数据进行预处理的基础上,结合MODIS土地利用产品和平滑滤波算法,构建耕地类型像元的I_LSW和I_NDV时相变化曲线。依据I_LSW和I_NDV曲线在水稻移栽期前后的变化规律,并根据由各地区水稻I_NDV时相曲线计算得到水稻相似性指数,从MODIS影像中提取水稻像元。采用FastICA算法对潜在水稻像元水稻生长期内的I_NDV时相曲线进行分解,计算每个像元的水稻丰度,绘制水稻丰度图,获取研究区各省水稻分布和种植面积。利用统计年鉴数据和样方资料对FastICA算法提取的水稻面积进行了验证。结果显示:采用水稻相似性曲线有利于提高稻田识别效率,所获取的水稻分布与实际情况吻合;FastICA算法能够分解不同地区水稻I_NDV时相曲线;与统计资料比较,江苏、安徽、江西三省水稻面积的提取精度分别为86.4%、87.9%、51.5%。江西水稻面积提取误差主要出现在地形起伏较大的山区。