采用混合整数计算方法处理配电系统事故自动恢复问题

当电力系统发生故障时 ,对停电区域进行最优化操作从而尽快恢复送电是十分重要的。对系统恢复送电的操作 ,分支限定法是一种典型的方法。

基坑工程的水土压力混合算法

水土压力计算是基坑支护工程设计的重要问题。针对中等透水性的土 ,本文提出了水土压力混合算法 ,并通过算例进行了讨论分析。

模型参数优化中的混合方法及其应用

归纳了现代典型混合软计算法的构成,指出其或松或紧融合多种单一要素来提供具有互补性的推理与搜索方法,是解决知识驱动推理或纯数据驱动推理问题的有效变通手段。通过知识域与经验数据的结合增加了模型可靠度和问题解决能力。为了解决最广泛和高复杂性的工程或社会问题,应开发有效整合各类推理搜索技术的智能工具箱,以获得低成本解决方案,并举例说明了混合软计算的应用。

T型三通水管路噪声特性数值研究

水管路系统工作运行中会产生较大的管路振动和流噪声。作为偶极子声源,充液管路内湍流激发的脉动压力会形成流噪声,且激励管壁产生流激振动噪声。为了揭示水管道系统的流激振动噪声与流噪声特性的区别,基于有限元方法对不同厚度的充液管路声学模态、结构模态以及耦合模态进行计算;基于计算流体力学联合声学边界元的混合计算方法探讨变流速下流噪声与管路声学特性之间的关系;并计算分析变流速下流噪声与流激振动噪声特性,变厚度下流激振动噪声特性;将变流速及变厚度管路的流噪声和流激振动噪声进行对比。结果表明:流噪声的峰值频率受管路声学模态的影响,随着流速的增加流噪声能量会增加但峰值频率不变;而流激振动噪声的峰值受管路耦合模态的影响,厚度增加导致模态变化,峰值频率改变;流噪声幅值要大于流激振动噪声幅值。

不等厚激光拼焊板焊缝处力学性能的试验研究

结合组成某轿车车身侧围内板的3种不同厚度的激光拼焊板,首先进行了单向拉伸试验,得到了3种拼焊板的基本力学性能参数。在试验的基础上,提出了基于"混合计算法"求解不等厚激光拼焊板焊缝处材料的力学性能的方法,并与试验结果进行对比,对这种计算方法中误差产生的原因进行了分析。

干式空芯电抗器涡流损耗分析

在比较解析法、数值计算法和混合计算法三种方法的基础上，采用混合计算法，对干式空芯电抗器的涡流损耗进行了较为详细的分析和计算．为进一步研究电抗器的温度分布提供了理论基础．

HYBRID MULTI-OBJECTIVE GRADIENT ALGORITHM FOR INVERSE PLANNING OF IMRT

The intelligent optimization of a multi-objective evolutionary algorithm is combined with a gradient algorithm. The hybrid multi-objective gradient algorithm is framed by the real number. Test functions are used to analyze the efficiency of the algorithm. In the simulation case of the water phantom, the algorithm is applied to an inverse planning process of intensity modulated radiation treatment （IMRT）. The objective functions of planning target volume （PTV） and normal tissue （NT） are based on the average dose distribution. The obtained intensity profile shows that the hybrid multi-objective gradient algorithm saves the computational time and has good accuracy, thus meeting the requirements of practical applications.

Dimension-down iterative algorithm for the mixed transportation network design problem

An optimal dimension-down iterative algorithm （DDIA） is proposed for solving a mixed （continuous/ discrete） transportation network design problem （MNDP）, which is generally expressed as a mathematical programming with equilibrium constraints （MPEC）. The upper level of the MNDP aims to optimize the network performance via both the expansion of existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium （UE） model. The idea of the proposed DDIA is to reduce the dimensions of the problem. A group of variables （discrete/continuous） are fixed to altemately optimize another group of variables （continuous/discrete）. Some continuous network design problems （CNDPs） and discrete network design problems （DNDPs） are solved repeatedly until the optimal solution is obtained. A numerical example is given to demonstrate the efficiency of the proposed algorithm.

Geometric Mean Decomposition Based Hybrid Precoding for Millimeter-Wave Massive MIMO

Hybrid precoding can reduce the number of required radio frequency(RF)chains in millimeter-Wave(mmWave) massive MIMO systems. However, existing hybrid precoding based on singular value decomposition(SVD) requires the complicated bit allocation to match the different signal-to-noise-ratios(SNRs) of different sub-channels. In this paper,we propose a geometric mean decomposition(GMD)-based hybrid precoding to avoid the complicated bit allocation. Specifically,we seek a pair of analog and digital precoders sufficiently close to the unconstrained fully digital GMD precoder. To achieve this, we fix the analog precoder to design the digital precoder, and vice versa. The analog precoder is designed based on the orthogonal matching pursuit(OMP) algorithm, while GMD is used to obtain the digital precoder. Simulations show that the proposed GMD-based hybrid precoding achieves better performance than the conventional SVD-based hybrid precoding with only a slight increase in complexity.

A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine

The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.

A Modified Mixing Rule for PSRK Model and Application for the Prediction of Vapor-Liquid Equilibria of Polymer Solutions

To extend the PSRK (predictive Soave-Redlich-Kwong equation of state) model to vapor-liquid equilibria of polymer solutions, a new EOS-gE mixing rule is applied in which the term ∑ xi ln(b/bi) in the PSRK mixing rule for the parameter a, and the combinatorial part in the original universal functional activity coefficient (UNIFAC) model are cancelled. To take into account the free volume contribution to the excess Gibbs energy in polymer solution, a quadratic mixing rule for the cross co-volume bij with an exponent equals to 1/2 is applied[bij1/2= 1/2(bi1/2+bj1/2)]. The literature reported Soave-Redlich-Kwong equation of state (SRK EOS) parameters ofpure polymer are employed. The PSRK model with the modified mixing rule is used to predict the vapor-liquid equilibrium (VLE) of 37 solvent-polymer systems over a large range of temperature and pressure with satisfactory results.

采煤机故障诊断及故障预测探讨

随着科学技术的不断发展,煤矿科学、安全生产是煤炭资源可持续发展的必要前提条件。目前,关于煤矿事件的发生层出不穷,如何保证煤矿机械设备安全、可靠的运行是当前煤炭行业面临的最主要的问题。而大型煤矿采煤所使用的机械设备主要是采煤机。但是采煤机经常工作的环境相当恶劣,所以极易出现设备故障问题。因此,对采煤机进行故障诊断及故障预测的探讨具有至关重要的现实意义。

Hybridizing artificial bee colony with biogeography-based optimization for constrained mechanical design problems

A novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony(ABC) algorithm with biogeography-based optimization(BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm's performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.

An evolutionary particle filter based EM algorithm and its application

In this paper, an evolutionary recursive Bayesian estimation algorithm is presented, which incorporates the latest observation with a new proposal distribution, and the posterior state density is represented by a Gaussian mixture model that is recovered from the weighted particle set of the measurement update step by means of a weighted expectation-maximization algorithm. This step replaces the resampling stage needed by most particle filters and relieves the effect caused by sample impoverishment. A nonlinear tracking problem shows that this new approach outperforms other related particle filters.

Introduction and evaluation of a novel hybrid brattice for improved dust control in underground mining faces: A computational study

A proper control and management of dust dispersion is essential to ensure safe and productive underground working environment. Brattice installation to direct the flow from main shaft to the mining face was found to be the most effective method to disperse dust particle away from the mining face. However,it limits the movement and disturbs the flexibility of the mining fleets and operators at the tunnel. This study proposes a hybrid brattice system- a combination of a physical brattice together with suitable and flexible directed and located air curtains- to mitigate dust dispersion from the mining face and reduce dust concentration to a safe level for the working operators. A validated three-dimensional computational fluid dynamic model utilizing Eulerian–Lagrangian approach is employed to track the dispersion of dust particle. Several possible hybrid brattice scenarios are evaluated with the objective to improve dust management in underground mine. The results suggest that implementation of hybrid brattice is beneficial for the mining operation: up to three times lower dust concentration is achieved as compared to that of the physical brattice without air curtain.

Mining Frequent Closed Itemsets in Large High Dimensional Data

Large high-dimensional data have posed great challenges to existing algorithms for frequent itemsets mining.To solve the problem,a hybrid method,consisting of a novel row enumeration algorithm and a column enumeration algorithm,is proposed.The intention of the hybrid method is to decompose the mining task into two subtasks and then choose appropriate algorithms to solve them respectively.The novel algorithm,i.e.,Inter-transaction is based on the characteristic that there are few common items between or among long transactions.In addition,an optimization technique is adopted to improve the performance of the intersection of bit-vectors.Experiments on synthetic data show that our method achieves high performance in large high-dimensional data.

Inverse procedure for determining model parameter of soils using real-coded genetic algorithm

The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.

Numerical simulation of stirred tanks using a hybrid immersed-boundary method

Conventionally, multiple reference frame(MRF) method and sliding mesh(SM) method are used in the simulation of stirred tanks, however, both methods have limitations. In this study, a hybrid immersed-boundary(IB)technique is developed in a finite difference context for the numerical simulation of stirred tanks. IBs based on Lagrangian markers and solid volume fractions are used for moving and stationary boundaries, respectively, to achieve optimal efficiency and accuracy. To cope with the high computational cost in the simulation of stirred tanks, the technique is implemented on computers with hybrid architecture where central processing units(CPUs) and graphics processing units(GPUs) are used together. The accuracy and efficiency of the present technique are first demonstrated in a relatively simple case, and then the technique is applied to the simulation of turbulent flow in a Rushton stirred tank with large eddy simulation(LES). Finally the proposed methodology is coupled with discrete element method(DEM) to accomplish particle-resolved simulation of solid suspensions in small stirred tanks. It demonstrates that the proposed methodology is a promising tool in simulating turbulent flow in stirred tanks with complex geometries.

Numerical simulation of asphalt mixture based on three-dimensional heterogeneous specimen

In order to verify the validity of finite element numerical simulation method for asphalt mixture, which consists of aggregates, mastic （where mastic is a kind of fine mixture composed of asphalt binder mixed with fines and fine aggregates） and air voids, based on three-dimensional （3D） heterogeneous specimen, X-ray computerized tomography （X-ray CT） was used to scan the asphalt specimens to obtain the real internal microstrnctures of asphalt mixture. CT images were reconstructed to build up 3D digital specimen, and the viscoelastic properties of mastic were described with Burgers model The uniaxial creep numerical simulations of three different levels of aggregate gradation were conducted. The simulation results agree well with the experimental results. The numerical simulation of asphalt mixture incorporated with real 3D microstructure based on finite element method is a promising application to conduct research of asphalt concrete. Additionally, this method can increase the mechanistic understanding of global viscoelastic properties of asphalt mixtures by linking the real 3D microstructure.