Misalignment analysis of journal bearing influenced by asymmetric deflection, based on a simple stepped shaft model

The effects of journal misalignment on a journal bearing caused by an asymmetric rotor structure are presented in this study.A new model considering the asymmetric deflection is applied.Also,the thermo-hydrodynamic of the oil film in the journal bearing and straightforward elasticity theory are considered in the analysis.Based on the structure stiffness equivalent characteristic,a simple stepped shaft can reflect the entire complex structure model.The existing lubrication model,which does not consider this angle component,is not very precise for journal bearings.Film pressure,misalignment angle,velocity field,oil leakage,and temperature field were calculated and compared in the journal bearing analysis.The results indicate that bearing performances are greatly affected by misalignment caused by the asymmetric structure.A simple stepped shaft can effectively represent a misaligned journal bearing in a rotor-bearing system.     

Experiment and Simulations on Lubrication Performance of EMP Journal Bearing

In recent years, much attention has been devoted to the design and operation of bearings made of elastic metal plastic (EMP). The surface of the bearing bush is covered by a layer of polymer PTFE(polytetrafluoroethylene). The physical performances of the polymer are quite different from that of metal. It can reduce friction because of its lower surface energy, and it is more difficult for the fluid to be adhered. Consequently, the slip will exist at the oil-bush interface. The journal bearings made of this material are researched in this article. Through test, the existence of slip is proven and the equation of the slip velocity for the EMP journal bearing is established when shear stress up to a certain value. Thus, the classical Reynolds equation is modified. The lubrication mechanism is analyzed by some simulation results.     

基于遗传机制的蚁群算法求解连续优化问题

A new algorithm is presented by using the ant colony algorithm based on genetic method (ACG) to solve the continuous optimization problem.Each component has a seed set.The seed in the set has the value of component,trail information and fitness.The ant chooses a seed from the seed set with the possibility determined by trail information and fitness of the seed.The genetic method is used to form new solutions from the solutions got by the ants.Best solutions are selected to update the seeds in the sets and trail information of the seeds.In updating the trail information,a diffusion function is used to achieve the diffuseness of trail information.The new algorithm is tested with 8 different benchmark functions.     

Interior-point algorithm based on general kernel function for monotone linear complementarity problem

A polynomial interior-point algorithm is presented for monotone linear complementarity problem (MLCP) based on:a class of kernel functions with the general barrier term, which are called general kernel functions. Under the mild conditions for the barrier term, the complexity bound of algorithm in terms of such kernel function and its derivatives is obtained. The approach is actually an extension of the existing work which only used the specific kernel functions for the MLCP.     

基于质粒模型的DNA计算机算法求解背包问题

本研究在穷举法的背包策略的基础上借鉴二表算法的思路,应用求解最大团问题的思路计算DNA计算机的NP完全计算问题。使用这种算法,能将DNA分子计算的维数从60扩大至120,这种算法的DNA链数可达亚指数的O(1 414n),这种算法拓展了穷举法背包策略的限制,使DNA计算机NP完全问题算法优化。     

Algorithm for 2D irregular-shaped nesting problem based on the NFP algorithm and lowest-gravity-center principle

INTRODUCTION 2D irregular-shaped nesting problem is the problem of finding an efficient arrangement for pieces in a containing region without overlapping (Fig.1), and is aimed at maximizing use of material. Nesting problem is of great interest to garment, paper, ship building, and sheet metal industries since small improvement of layout can lead to large savings in material. Many effective solutions have been pro- posed for the case when pieces and containing region are both rectangular. …     

Algorithm for 2D irregular-shaped nesting problem based on the NFP algorithm and lowest-gravity-center princlple

The nesting problem involves arranging pieces on a plate to maximize use of material. A new scheme for 2D irregular-shaped nesting problem is proposed. The new scheme is based on the NFP （No Fit Polygon） algorithm and a new placement principle for pieces. The novel placement principle is to place a piece to the position with lowest gravity center based on NFP. In addition, genetic algorithm （GA） is adopted to find an efficient nesting sequence. The proposed scheme can deal with pieces with arbitrary rotation and containing region with holes, and achieves competitive results in experiment on benchmark datasets.     

Optimal parallel algorithm for shortest-paths problem on interval graphs

This paper presents an efficient parallel algorithm for the shortest-path problem in interval graph for computing shortest-paths in a weighted interval graph that runs in O(n) time with n intervals in a graph. A linear processor CRCW algorithm for determining the shortest-paths in an interval graphs is given.     

Optimal parallel algorithm for shortest-paths problem on interval graphs

This paper presents an efficient parallel algorithm for the shortest-path problem in interval graph for computing shortest-paths in a weighted interval graph that runs in O(n) time with n intervals in a graph. A linear processor CRCW algorithm for determining the shortest-paths in an interval graphs is given.     

Heuristic algorithm for off-lattice protein folding problem

Enlightened by the law of interactions among objects in the physical world, we propose a heuristic algorithm for solving the three-dimensional （3D） off-lattice protein folding problem. Based on a physical model, the problem is converted from a nonlinear constraint-satisfied problem to an unconstrained optimization problem which can be solved by the well-known gradient method. To improve the efficiency of our algorithm, a strategy was introduced to generate initial configuration. Computational results showed that this algorithm could find states with lower energy than previously proposed ground states obtained by nPERM algorithm for all chains with length ranging from 13 to 55.     

一种求解RSMT布线问题的PSO算法

最小直角斯坦纳树（RSMT）问题是超大规模集成电路布线中的重要问题之一,是典型的NP困难组合优化问题.为了有效地解决超大规模集成电路布线中的RSMT问题,提出一种粒子群优化算法,借助直角Steiner树的一些性质,采用Steiner点编码方案,寻找优化的Steiner点位置以减少直角Steiner树的长度.对几组布线模型实例进行了仿真测试,表明了该算法的有效性.     

一个SNP问题的多项式时间算法

讨论关于单体型的无间隙的最小单核苷酸多态性位点的移去问题.通过分析其对应图模型的性质讨论问题等价形式;证明求解该问题等价于求对应图的最大独立集与独立数;给出求最大独立集与独立数的算法,从而得到此问题的有效的多项式时间算法.     

一类Jacobi矩阵特征值反问题的新算法

In this paper, an inverse problem on Jacobi matrices presented by Shieh in 2004 is studied. Shieh’s result is improved and a new and stable algorithm to reconstruct its solution is given. The numerical examples is also given.     

Smoothing newton algorithm for solving generalized complementarity problem

The generalized complementarity problem includes the well-known nonlinear complementarity problem and linear complementarity problem as special cases.In this paper, based on a class of smoothing functions, a smoothing Newton-type algorithm is proposed for solving the generalized complementarity problem.Under suitable assumptions, the proposed algorithm is well-defined and global convergent.     

Efficient genetic algorithm for resource-constrained project scheduling problem

This paper presents a new genetic algorithm for the resource-constrained project scheduling problem(RCPSP).The algorithm employs a standardized random key(SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme(SGS) is to be used as the decoding procedure.The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions to schedule the project three times and obtain an SRK vector,which is rese...     

Algorithm for solving the bi-level decision making problem with continuous variables in the upper level based on genetic algorithm

1 Introduction a The bi-level decision-making is a complex majorized problem. Its effective solution is not easy to obtain by traditional majorized methods. Reported methods to solve the bi-level decision making problem with continuous variables include neural network [1], Monte Carlo simulated annealing algorithm [2], etc. However, the efficiency and accuracy of such neural network methods are ideal and accompanied with a long iterative time and a slow convergence speed. In this paper, the …     

基于蚁群算法的医用服务机器人路径规划方法

机器人路径规划问题是机器人学的一个重要研究领域，主要研究机器人依据某个或某些优化原则，在其工作空间中找到一条从起始点到目标点的能避开障碍物的最优路径。国内外学者对此作过大量的研究，主要采用的方法有局部的人工势场法(Artificial Potential Field)和遗传算法(cene     

一类线性不等式约束优化问题的信赖域算法

对一类带有非负边界约束的线性不等式约束优化问题提出了一种新的信赖域算法。此算法以内点法为基础,把非负边界约束从一般的不等式约束中分离出来,化为信赖域约束的一部分,从而得到一个简单易解的子问题。在一定的条件下证明了算法的收敛性,并给出了数值结果。     

基于内嵌Word技术的学报稿件管理系统方案

对大学学报稿件管理的业务流程进行了较为全面系统的分析,提出了采用内嵌Word技术解决以往学报稿件管理系统不能很好处理稿件文档的瓶颈,同时基于工作流建立全流程全在线的管理模式,减轻编辑部繁重的工作,并在作者、编辑部、审稿专家之间建立了通畅的管理渠道。     

《高等教育研究》2002-2006年被引研究——基于CSSCI的分析

利用CSSCI数据库对《高等教育研究》2002-2006年刊载文章的被引情况与相关高等教育刊物的对比分析显示,其被引用率、篇均被引和期刊自引率明显高于同类刊物,引用期刊多为全国中文核心期刊。选题具有稳定性、连续性和创新性。该刊影响程度高,传播范围广,在我国高教领域的领先地位十分突出。