无网格方法中含参数指数权函数的研究

选择合适的权函数及相应的影响半径是无网格方法中很重要的问题,在引入数值紧支域概念的基础上分析了含参数的指数权函数中参数的选取范围,综合考虑计算效率和精度后给出了参数的选取原则,并讨论了在特定的参数下的最优半径以及不同参数对最优半径的影响.     

M/G/1排队系统性能梯度估计的非标准分析法

如何估计系统性能梯度是离散事件动态系统研究中的一个重要问题.系统性能对于概率参数的梯度无法用传统的摄动分析法来估计,我们从非标准分析的角度提出了一种基于Dirac δ函数的摄动分析算法,分析了相应估计量的强相合性和渐近无偏性.新算法在实现过程中需要用样条函数来近似δ函数,但可以同时估计M/G/1排队系统中顾客期望系统时间和忙期期望长度对概率参数的梯度.数值实验结果表明估计量的相对误差和无偏性检验值都比较小,新算法能够很好地估计M/G/1排队系统的性能梯度.     

拓扑优化在机载计算机结构设计中的应用

为了解决机载计算机零件结构设计过程中出现的材料分布不合理及重量要求苛刻等问题，在设计过程中引入拓扑优化。介绍了基于变密度法的拓扑优化理论，以Hyperworks／Optistruct为拓扑优化分析平台，对某机载计算机零件进行了拓扑优化，确定了零件的最佳材料分布。结果表明：通过优化设计可以在保持零件基本结构性能的基础上减轻其重量。     

基于博弈均衡分析的电子战战法

用定量分析的方法开发电子战战法是海军战役规划中必须解决的重要问题.借助仿真和博弈分析的混合方法,在博弈效用函数计算的基础上,构建基于识别真、假目标以及火力命中目标概率的二人非零和(TPNZS)非合作博弈模型来开发电子战战法,对一个典型的舰载导弹防空系统的初步研究表明:电子进攻与电子防御的战法分别为π*=(0,π*2,1-π*2)=(0.0000,0.5890,0.4110)和Δ*=(0.0000,0.0000,Δ*3)=(0.0000,0.0000,1.0000).     

河南省人力资本与经济增长的关系

河南的人力资本与经济发展相互影响、相互制约,具有密切的联系.人力资本对经济发展的促进作用是显而易见的,但经济的快速增长并没有带来人力资本存量的相应增加,这与多年来执行的经济政策是一致的.无论是在省际层面还是省内层面,河南人力资本与经济发展之间存在着不一致性,人力资本的培育和发展具有较大的不平衡性.从人力资本的结构上看,不同类型的人力资本与经济之间的相互关系呈现出多样性.     

《高频电子线路》课程“相乘器”教学策略

相乘器是高频电子线路课程中的一个重要单元电路。掌握相乘器的组成、基本原理、分析方法以及器件特点是通信电子信息类学生学好调制、检波以及混频电路的关键所在,讨论非线性器件二极管在开关状态下组成"相乘器"的教学策略对教学活动具有重要意义。     

A hybrid lattice Boltzmann flux solver for integrated hypersonic fluid-thermal-structural analysis

In this paper, a hybrid Lattice Boltzmann Flux Solver (LBFS) with an improved switch function is proposed for simulation of integrated hypersonic fluid-thermal-structural problems. In the solver, the macroscopic Navier–Stokes equations and structural heat transfer equation are discretized by the finite volume method, and the numerical fluxes at the cell interface are reconstructed by the local solution of the Boltzmann equation. To compute the numerical fluxes, two equilibrium distribution functions are introduced. One is the D1Q4 discrete velocity model for calculating the inviscid flux across the cell interface of Navier–Stokes equations, and the other is the D2Q4 model for evaluating the flux of structural energy equation. In this work, a new dual thermal resistance model is proposed to calculate the thermal properties at the fluid–solid interface. The accuracy and stability of the present hybrid solver are validated by simulating several numerical examples, including the fluid-thermal-structural problem of cylindrical leading edge. Numerical results show that the present solver can accurately predict the thermal properties of hypersonic fluid-thermal-structural problems and has the great potential for solving fluid-thermal-structural problems of long-endurance high-speed vehicles.     

An adaptive sequential experiment design method for model validation

Efficient experiment design is of great significance for the validation of simulation model with high nonlinearity and large input space. Excessive validation experiment raises the cost while insufficient test increases the risks of accepting an invalid model. In this paper, an adaptive sequential experiment design method combining global exploration criterion and local exploitation criterion is proposed. The exploration criterion utilizes discrepancy metric to improve the space-filling property of the design points while the exploitation criterion employs the leave one out error to discover informative points. To avoid the clustering of samples in the local region, an adaptive weight updating approach is provided to maintain the balance between exploration and exploitation. Besides, the credibility distribution function characterizing the relationship between the input and result credibility is introduced to support the model validation experiment design. Finally, six benchmark problems and an engineering case are applied to examine the performance of the proposed method. The experiments indicate that the proposed method achieves satisfactory performance for function approximation in accuracy and convergence.     

An optimal selection of probability distribution functions for unsupervised land cover classification of PALSAR-2 data

Different types of classification techniques are available in the literature for the classification of Synthetic Aperture Radar (SAR) data into various land cover classes. Various SAR images are available for land cover classification such as ALOS PALSAR (PALSAR-1, PALSAR-2), RADARSAT and ENVISAT. In this paper, we have attempted to explore probability distribution function (pdf) based land cover classification using PALSAR-2 data. Over 20 different statistical distribution functions are analyzed for different classes based on statistical parameters. Probability distribution functions are selected based on Chi-squared goodness of fit test for each individual class. A decision tree based classifier is developed for classification based on the selected pdf functions and its statistical parameters. The proposed classification approach has an accuracy of 83.93%.