High velocity flow simulation using lattice Boltzmann method with no-free-parameter dissipation scheme

A finite difference lattice Boltzmann method of second-order accuracy in time is developed based on non-oscillatory scheme with no-free-parameter dissipation (NND) difference scheme in this paper. The NND lattice Boltzmann method is used to simulate high-speed flows by constructing a new equilibrium distribution function of the lattice Boltzmann method.Compared with a variation of lattice Boltzmann method developed by Qu, et al., the present method can capture shock waves and handle oscillations of high velocity flows accurately in larger time steps and in shorter computing time. Numerical results indicate the correctness and capability of simulating shock wave interactions of the NND lattice Boltzmann method.     

Simulation of two-phase flows of a droplet impacting on a liquid film with an improved lattice Boltzmann model

Based on the lattice Boltzmann method (LBM), an improved pseudo-potential model, combined with a method of adding force term, is used to simulate the two-phase flows caused by a liquid droplet impacting on a liquid film. In this model, the different phases are treated as one fluid, and the interfaces between the vapor and liquid phases can be obtained by density value of the fluid. This variant of the LBM allows one to obtain the densities of vapor and liquid with high accuracy. The model is validated by an example of phase separation. The early stage of the impact of droplet on liquid film is simulated, and the results are qualitatively consistent with physical phenomena.     

Modified surface tension model for free surface flow with single-phase lattice Boltzmann method

A single-phase lattice Boltzmann model with modified surface tension is developed in this paper to solve the problem of high-density-ratio free surface flow.The computational efficiency and accuracy are both enhanced.The restriction to the relaxation factor （which needs to be smaller than 1） is circumvented by the new surface tension algebra,due to its rational physical nature compared with the treatment of Xing,Buther and Yang in their paper （Comp.Mater.Sci.,2007,39（2）：282-290）.The proposed stable surface tension scheme is applied to simulate the free deformation of a square droplet with surface tension effect and the process of a droplet impinging on a liquid film.The numerical solution for free deformation of a droplet agrees well with thermodynamic principles,and also achieves high accuracy in comparison with Xing,et al.＇s model.Three typical impinging modes are successfully obtained with the new scheme,and another particular mode found by Wang and Chen is also successfully simulated.The evolutions of liquid crown agree well with the power law related to time.     

Comparision of DdQm models in image optical flow analysis based on LBM

The optical flow analysis of the image sequence based on the formal lattice Boltzmann equation, with different DdQm models, is discussed in this paper. The algorithm is based on the lattice Boltzmann method (LBM), which is used in computational fluid dynamics theory for the simulation of fluid dynamics. At first, a generalized approximation to the formal lattice Boltzmann equation is discussed. Then the effects of different DdQm models on the results of the optical flow estimation are compared with each other, while calculating the movement vectors of pixels in the image sequence. The experimental results show that the higher dimension DdQm models, e.g., D3Q15 are more effective than those lower dimension ones.     

基于PVM的并行计算

利用PvM（Parallel Virtual Machine）并行计算环境,使用Visual C＋＋为开发工具,针对大型矩阵的运算开发了并行处理系统,解决了机械、数学等领域对大型矩阵运算处理时耗时时间长,界面交互性差等问题。     

Parallel computing for finite element structural analysis using conjugategradient method based on domain decomposition

1 Introduction Large and complex engineering problems often needmuch computation ti me and storage to run on ordinaryuniprocessor computers . Even if they can be solved ,powerful computation capability is required to obtainaccurate and reliable results within reasonable ti me .Parallel computing can meet requirements of high per-formance computing[1].Various types of parallel hard-ware architectures have been developed and parallelalgorithms adapted to these hardware architecturesproposed[2 ,3…     

基于区域分解的共轭梯度法的有限元结构分析并行计算

1 Introduction Large and complex engineering problems often needmuch computation ti me and storage to run on ordinaryuniprocessor computers . Even if they can be solved ,powerful computation capability is required to obtainaccurate and reliable results within reasonable ti me .Parallel computing can meet requirements of high per-formance computing[1].Various types of parallel hard-ware architectures have been developed and parallelalgorithms adapted to these hardware architecturesproposed[2 ,3…     

基于一个新核函数的半定规划的内点算法的复杂性分析

Interior-point methods （IPMs） for linear optimization （LO） and semidefinite optimization （SDO） have become a hot area in mathematical programming in the last decades. In this paper, a new kernel function with simple algebraic expression is proposed. Based on this kernel function, a primal-dual interior-point methods （IPMs） for semidefinite optimization （SDO） is designed. And the iteration complexity of the algorithm as O（n^3/4 log n/ε） with large-updates is established. The resulting bound is better than the classical kernel function, with its iteration complexity O（n log n/ε） in large-updates case.     

Study on One—Dimensional Model of Traffic Flow with Stochastic Deceleration via Lattice Boltzmann Method

One-dimensional traffic model was studied with the consideration of stochastic deceleration by using the lattice Boltzmannmethod.The evolution equation for vehicle density was derived,which has the form of the Burgers equation exhibiting the effect of viscosity corresponding to the deceleration.The simulation with the model shows that the variation of vehicle density in space tends to a periodic one,which implies the existence of kinematic waves in the 1D traffic flow and coincides with theoretical prediction.     

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.     

基于快速并行优化算法的非线性预测控制

从建立稳定、精确的非线性预测模型出发,以Broyden,Fletcher,Goldfarb和Sharmo(BFGS)的拟牛顿优化算法为基础,在神经网络的训练过程中引入两个含有不同参数的拟牛顿校正公式并行的确定搜索方向,通过不精确搜索法求取最优步长,最后根据性能指标取最优的一个搜索方向和相应的步长对网络各层之间的权值进行修正。控制器采用神经网络递推多步预测、自补偿式在线闭环反馈校正以及迭代学习求解进行优化的方法。Matlab仿真结果验证了该方法的有效性。     

Optimal choice of parameters for particle swarm optimization

INTRODUCTION Particle swarm optimization (PSO) is one of the evolutionary computational techniques. Since its introduction (Kennedy and Eberhart, 1995; Eberhart and Kennedy, 1995; Eberhart et al., 1996), PSO has attracted much attention from researchers around the world. It is a population-based search algorithm and is initialized with a population of random solutions, called particles. Each particle in PSO moves over the search space at velocity dynamically adjusted according to th…     

An approach for shape optimization of stratosphere airships based on multidisciplinary design optimization

Airship shape is crucial to the design of stratosphere airships. In this paper, multidisciplinary design optimization （MDO） technology is introduced into the design of airship shape. We devise a composite objective function, based on this technology, which takes account of various factors which influence airship performance, including aerodynamics, structures, energy and weight to determine the optimal airship shape. A shape generation algorithm is proposed and appropriate mathematical models are constructed. Simulation results show that the optimized shape gives an improvement in the value of the composite objective function compared with a reference shape.     

A new optimization algorithm based on chaos

INTRODUCTION Chaos (Wang et al., 2002) is a common nonlin- ear phenomenon, whose action is complex and similar to that of randomness. The characteristics of chaos being highly sensitive to the initial value of chaos make a world of differences due to the ergodic prop- erty of the phase space—chaos can go through all states in certain ranges without repetition; the inher- ent randomness of the system—means that chaos behavior is similar to randomness which is disorderly; but at the same t…     

MIC商用并行编程性能优化分析

针对MIC架构处理各种复杂业务时对性能日益增长的要求,为充分利用MIC使用已有编程模型的优势,通过避免内存容量、网络带宽方面的瓶颈增强并行编程的线程扩展性,对并行度、内存空间、数据通信与传递、Cache访问、负载均衡以及循环分块和向量化等方法进行了讨论。通过在内存数据库领域优化性能的应用,对使用三层优化方法发挥MIC众核技术优势进行了分析与展望。     

In-package P/G planes analysis and optimization based on transmission matrix method

Power integrity （PI） has become a limiting factor for the chip＇s overall performance, and how to place in-package decoupling capacitors to improve a chip＇s PI performance has become a hot issue. In this paper, we propose an improved transmission matrix method （TMM） for fast decoupling capacitance allocation. An irregular grid partition mechanism is proposed, which helps speed up the impedance computation and complies better with the irregular power/ground （P/G） plane or planes with many vias and decoupling capacitors. Furthermore, we also ameliorate the computation procedure of the impedance matrix whenever decoupling capacitors are inserted or removed at specific ports. With the fast computation of impedance change, in-package decoupling capacitor allocation is done with an efficient change based method in the frequency domain. Experimental results show that our approach can gain about 5× speedup compared with a general TMM, and is efficient in restraining the noise on the P/G plane.     

凸二次规划的一个新原-对偶内点算法

In this paper, a new primal-dual interior-point algorithm for convex quadratic optimization (CQO) based on a kernel function is presented. The proposed function has some properties that are easy for checking. These properties enable us to improve the polynomial complexity bound of a large-update interior-point method (IPM) to O (√nlognlogn/ε), which is the currently best known polynomial complexity bound for the algorithm with the large-update method. Numerical tests were conducted to investigate the behavior of the algorithm with different parameters p, q and θ, where p is the growth degree parameter, q is the barrier degree of the kernel function and θ is the barrier update parameter.     

Reliability based multiobjective optimization for design of structures subject to random vibrations

Based on a multiobjective approach whose objective function （OF） vector collects stochastic reliability performance and structural cost indices, a structural optimization criterion for mechanical systems subject to random vibrations is presented for supporting engineer＇s design. This criterion differs from the most commonly used conventional optimum design criterion for random vibrating structure, which is based on minimizing displacement or acceleration variance of main structure responses, without considering explicitly required performances against failure. The proposed criterion can properly take into account the design-reliability required performances, and it becomes a more efficient support for structural engineering decision making. The multiobjective optimum （MOO） design of a tuned mass damper （TMD） has been developed in a typical seismic design problem, to control structural vibration induced on a multi-storey building structure excited by nonstationary base acceleration random process A numerical example for a three-storey building is developed and a sensitivity analysis is carried out. The results are shown in a useful manner for TMD design decision support.     

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K- means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization （PSO） and simulated annealing （SA）. The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley＇s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.     

Nearest neighbor search algorithm based on multiple background grids for fluid simulation

The core of smoothed particle hydrodynamics (SPH) is the nearest neighbor search subroutine. In this paper, a nearest neighbor search algorithm which is based on multiple background grids and support variable smooth length is introduced. Through tested on lid driven cavity flow, it is clear that this method can provide high accuracy. Analysis and experiments have been made on its parallelism, and the results show that this method has better parallelism and with adding processors its accuracy become higher, thus it achieves that efficiency grows in pace with accuracy.