降雨入渗过程的水-气二相流模型研究

本文根据多孔介质中水、气的质量守恒定律，结合多相流理论，建立了求解饱和-非饱和渗流的水-气二相流数学模型，并采用积分形式的有限差分法和NewtonRaphson迭代方法进行数值求解，提出了各种边界条件，包括水相、气相和降雨入渗边界的数学处理方法。利用上述模型对土柱试验进行模拟，将计算结果与试验数据比较，验证了模型的正确性；然后对土质边坡降雨入渗过程进行计算，得到孔隙水压力、孔隙气压力和毛细压力的变化过程，其变化规律符合实际，实现了降雨入渗的水-气二相渗流过程，为定量研究空气阻力对入渗水流的影响提供有效途径。     

基于VS的分形图形绘制

根据牛顿迭代法生成分形图形的原理,在Visual Studio平台下实现了用窗口获得不同参数来实现同一程序绘制不同分形图形,解决了以往用C语言编写程序,特定程序只能绘制特定分形图形的问题。同时对牛顿迭代算法进行改进,加快了生成分形图形的速度。并采用对scale和stretch参数进行控制替代以往对xmax‘,xmin’,ymax‘,ymin参数的控制使得对绘制分形图形的精细程度的控制更加直观。     

基于牛拉法的预估校正潮流计算算法

为了减少迭代次数,提高收敛性,在一阶牛顿拉夫逊法基础上对不平衡量ΔP和ΔQ进行修正,采用一阶牛顿法得到的修正量作为预测量,利用节点注入电流方程和电压方程形成不平衡量的校正值,从而得到新的修正方程,沿用传统牛顿法进行迭代计算。从理论上讲该方法具有三阶收敛性。通过对典型IEEE节点实例进行Matlab编程仿真,与传统牛拉法做对比,该方法具有迭代次数少,收敛性好,编程量增加不多的特点。     

一种改进的牛顿-拉夫森算法

为了保证牛顿一拉夫森算法中迭代所采用的二阶导数矩阵的正定性,进一步改善算法的收敛速度和迭代精度,提出了两个方面的改进:一方面,对二阶导数矩阵作了修正以确保其成为正定矩阵,从而改善了收敛速度;另一方面,引入了一个修正因子对每次迭代的结果加以修正,来提高迭代精度.仿真结果表明,改进的牛顿一拉夫森算法所得到的结果精度更高,而且收敛速度也有所提高,也验证了改进方法的正确性和有效性.     

中压不接地配电网三相潮流新方法

在大量分布式电源接入中低压配电网的新形势下,三相潮流计算是分析其影响的基本手段。针对现有中压不接地配电网三相潮流研究主要采用人为设置参考中性点/零序电压的方式,导致无法仿真分析中性点/零序电压偏移、不接地网络零序潮流和相-地电压不平衡等情况,提出一种中压不接地配电网三相潮流新算法。首先,提出不接地配电网三相潮流在节点变量和导纳矩阵方面的特殊性。然后,设计基于功率平衡方程和牛拉法,采用导纳矩阵可逆化处理和矩阵替换技术实现约束零序电流为零的不接地配电网三相潮流算法。最后,基于6节点系统和修改的IEEE123算例仿真不接地配网的潮流,结合PSCAD验证所提方法在不同场景下的准确性以及在大电网中的适用性和收敛性,并在地市电网中进行实际应用。算例分析表明,所提算法计算结果准确,具有良好的工程实用性。     

快速高精度除法算法的FPGA实现

为在现场可编程门阵列(FPGA)中实现快速高精度除法,在传统的倒数除法的基础上,提出一种改进算法.对倒数求解采用泰勒级数展开结合优化搜索逼近,求出各个分区间内的拟合一次两项式,再通过一次牛顿迭代提高精度.时序仿真结果表明,以该算法构建的除法器易于在FPGA上实现,时延仅为6个时钟周期,能达到2(-34)的有效精度和86...     

Identification schemes for unmanned excavator arm parameters

Parameter identification is a key requirement in the field of automated control of unmanned excavators （UEs）. Furthermore, the UE operates in unstructured, often hazardous environments, and requires a robust parameter identification scheme for field applications. This paper presents the results of a research study on parameter identification for UE. Three identification methods, the Newton-Raphson method, the generalized Newton method, and the least squares method are used and compared for prediction accuracy, robustness to noise and computational speed. The techniques are used to identify the link parameters （mass, inertia, and length） and friction coefficients of the full-scale UE. Using experimental data from a full-scale field UE, the values of link parameters and the friction coefficient are identified. Some of the identified parameters are compared with measured physical values. Furthermore, the joint torques and positions computed by the proposed model using the identified parameters are validated against measured data. The comparison shows that both the Newton-Raphson method and the generalized Newton method are better in terms of prediction accuracy. The Newton-Raphson method is computationally efficient and has potential for real time application, but the generalized Newton method is slightly more robust to measurement noise. The experimental data were obtained in collaboration with QinetiQ Ltd.     

Accelerating the quadratic lower-bound algorithm via optimizing the shrinkage parameter

When the Newton-Raphson algorithm or the Fisher scoring algorithm does not work and the EM-type algorithms are not available, the quadratic lower-bound (QLB) algorithm may be a useful optimization tool. However, like all EM-type algorithms, the QLB algorithm may also suffer from slow convergence which can be viewed as the cost for having the ascent property. This paper proposes a novel ‘shrinkage parameter’ approach to accelerate the QLB algorithm while maintaining its simplicity and stability (i.e., monotonic increase in log-likelihood). The strategy is first to construct a class of quadratic surrogate functions Q_r(θ|θ^(t)) that induces a class of QLB algorithms indexed by a ‘shrinkage parameter’ r (r∈R) and then to optimize r over R under some criterion of convergence. For three commonly used criteria (i.e., the smallest eigenvalue, the trace and the determinant), we derive a uniformly optimal shrinkage parameter and find an optimal QLB algorithm. Some theoretical justifications are also presented. Next, we generalize the optimal QLB algorithm to problems with penalizing function and then investigate the associated properties of convergence. The optimal QLB algorithm is applied to fit a logistic regression model and a Cox proportional hazards model. Two real datasets are analyzed to illustrate the proposed methods.     

冷连轧机过程控制在线负荷分配方法

介绍了一种在线使用的冷连轧机负荷分配方法:通过查询数据库得到初始的负荷分配模式和负荷分配比,利用该负荷分配模式建立单目标负荷目标函数;采用简化的Newton Raphson法迭代求解非线性方程组,得到负荷分配的初始结果;根据第5机架轧制带钢长度对负荷分配结果进行修正,以克服轧制过程中带钢打滑现象;对负荷分配结果进行极限值的检查修正并最终确定负荷分配结果。该负荷分配方法用于在线,有较好的使用效果。     

Evaluation of the genetic algorithm performance for the optimization of the grand potential in the cluster variation method

Due to the importance of phase diagrams in a wide range of material based industries, additional efforts should be dedicated to their elaboration techniques. The cluster variation method is a promising technique to model the entropy within different plane lattices and is recognized by the materials physics community as a powerful modeling framework. Motivated by the efficiency of genetic algorithms in solving numerous types of optimization problems, our aim in this work is to investigate their performance in minimizing the grand potential in the context of the cluster variation method. A comparison is conducted with respect to numerical iterative techniques namely the Newton-Raphson and natural iteration methods, where many performance criteria are computed and compared. The obtained results allow the ranking of the considered approaches according to their performance measures and suggest a more profound investigation of metaheuristics particularly for complicated cluster structures in the future.