大型复杂铸件毛坯最佳适配算法的研究

针对大型复杂铸件毛坯与设计原形存在误差,提出了梯度-模拟退火算法来对铸件毛坯进行适配.本算法综合了梯度法与模拟退火算法各自优点,可使优化解不陷入局部极值解而获得全局最优解,从而实现毛坯的最佳适配.最后运用实例验证所提出的算法的可行性及有效性.     

液压混合动力工程车辆联合制动系统优化与仿真

针对液压混合动力工程车辆制动系统能量回收率较低的问题,以某混合动力装载机为原型对其联合制动系统中的再生制动系统进行分析,对影响系统能量回收率的主要参数采用遗传算法进行优化,并对优化过的系统在整车仿真模型中进行仿真验证。仿真结果表明:系统优化后车辆的能量回收率得到了显著的提高,达到了节能减排的目的。     

基于多传感器数据融合的液压泵故障诊断研究

将D—S证据理论应用于多传感器数据融合，提出了多传感器数据融合一般化方法，并将其应用于液压泵故障诊断。通过数据融合诊断结果与单传感器诊断结果的比较，证明多传感器数据融合能明显提高故障诊断的准确率。     

软黏土不排水循环应力应变关系的数值模拟

对程星磊等提出的总应力形式增量弹塑性本构模型进行二次开发,以模拟复杂应力状态下软黏土的响应。通过Newton-Raphson算法,对材料非线性问题进行迭代求解;针对本构模型中应力反向等一系列关键性问题,应用欧拉切线算法编写了有限元程序,并结合子增量方法提高了计算精度。预测了软黏土在轴对称应力状态下的响应,得到了应力应变关系曲线,将其与单元预测结果进行比较,二者趋于一致,从而验证了有限元程序编写的合理性。利用该程序模拟三轴不固结不排水试验,模拟结果与试验吻合良好,表明该本构模型有限元程序可以反映轴对称应力状态下软黏土的不排水应力应变特性,可应用于更加复杂边值问题的模拟计算。     

水轮发电机组的状态监测和故障诊断

水轮发电机组是水电厂的核心设备之一,其运行状态的稳定性与安全性直接关系到水电厂的安全。本文在分析水轮发电组振动机理、监测内容及典型故障的基础上,对水轮发电组的状态监测和故障诊断系统进行了阐述。     

Algorithms for generating random variables with a rational probability-generating function

Two algorithms for generating random variables with a rational probability-generating function are presented. One of them implements the recently developed general range reduction method, and the other is an extension of the alias method designed for generating discrete finite-valued random variables to the case where the generated random variable is infinite-valued. An example of a random variable which was efficiently generated by random number generators implementing the presented algorithms is given. Possible ways of improving the complexity of the presented algorithms are discussed.     

Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

Conditional diagnosability and strong diagnosability of shuffle-cubes under the comparison model

The growing size of multiprocessor systems increases the vulnerability to component failures. It is crucial to locate and replace faulty processors to maintain the system's high reliability. Processor fault diagnosis is essential to the reliability of a multiprocessor system and the diagnosabilities of many well-known networks (such as hierarchical hypercubes and crossed cubes [S. Zhou, L. Lin and J.-M. Xu, Conditional fault diagnosis of hierarchical hypercubes, Int. J. Comput. Math. 89(16) (2012), pp. 2152–2164 and S. Zhou, The conditional diagnosability of crossed cubes under the comparison model, Int. J. Comput. Math. 87(15) (2010), pp. 3387–3396]) have been investigated in the literature. A system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly t-diagnosable if it is t-diagnosable and can achieve (t+1)-diagnosability except for the case where a node's neighbours are all faulty. In addition, conditional diagnosability has been widely accepted as a new measure of diagnosability by assuming that any fault-set cannot contain all neighbours of any node in a multiprocessor system. In this paper, we determine the conditional diagnosability and strong diagnosability of an n-dimensional shuffle-cube SQ_n, a variant of hypercube for multiprocessor systems, under the comparison model. We show that the conditional diagnosability of shuffle-cube SQ_n (n=4k+2 and k≥2) is 3n?9, and SQ_n is strongly n-diagnosable under the comparison model.     

Numerical solution of nonlinear system of Klein–Gordon equations by cubic B-spline collocation method

A technique to approximate the solutions of nonlinear Klein–Gordon equation and Klein–Gordon-Schrödinger equations is presented separately. The approach is based on collocation of cubic B-spline functions. The above-mentioned equations are decomposed into a system of partial differential equations, which are further converted to an amenable system of ODEs. The obtained system has been solved by SSP-RK54 scheme. Numerical solutions are presented for five examples, to show the accuracy and usefulness of proposed approach. The approximate solutions of both the equations are computed without using any transformation and linearization. The technique can be applied with ease to solve linear and nonlinear PDEs and also reduces the computational work.