Cooling Load Density Analysis and Optimization for an Endoreversible Air Refrigerator

The performance analysis and optimization of an endoreversible air refrigerator is carried out by taking the cooling load density, which is defined as the ratio of cooling load to the maximum specific volume in the cycle, as the optimization objective in this paper. The results obtained are different from those with the cooling load objective. Numerical examples show the effects of pressure ratio and allocation of heat exchanger inventory on the cooling load density of the refrigerator.     

Power Density Optimization for an Irreversible Closed Brayton Cycle

In this paper, the power density, defined as the ratio of power output to the maximum specific volume in the cycle, is taken as objective for performance optimization of an irreversible closed Brayton cycle coupled to constant-temperature heat reservoirs in the viewpoint of finite time thermodynamics (FTT) or entropy generation minimization (EGM). The analytical formulas about the relations between power density and pressure ratio are derived with the heat resistance losses in the hot- and cold-side heat exchangers and the irreversible compression and expansion losses in the compressor and turbine. The maximum power density optimization is performed by searching the optimum heat conductance distribution corresponding to the optimum power density of the hot- and cold- side heat exchangers for the fixed heat exchanger inventory. The influence of some design parameters on the optimum heat conductance distribution, the maximum power density, and the optimum pressure ratio corresponding to the maximum power density are provided. The power plant design with optimization leads to a higher efficiency and smaller size including the compressor, turbine, and the hot- and cold-side heat exchangers.     

Ecological Optimization Performance of An Irreversible Quantum Otto Cycle Working with an Ideal Fermi Gas

The model of an irreversible Otto cycle using an ideal Fermi gas as the working fluid, which is called as the irreversible Fermi Otto cycle, is established in this paper. Based on the equation of state of an ideal Fermi gas, the ecological optimization performance of an irreversible Fermi Otto cycle is examined by taking an ecological optimization criterion as the objective, which consists of maximizing a function representing the best compromise between the exergy output and exergy loss (entropy production) of the cycle. The relationship between the ecological function E and the efficiency η is studied. Three special cases are discussed in detail. The results obtained herein may reveal the general performance characteristics of the irreversible Fermi Otto cycle.     

基于GRNN的冰蓄冷空调逐时冷负荷预测

冷负荷动态预测对冰蓄冷空调最优化控制来说是不可或缺的.建立了基于广义回归神经网络(GRNN)和遗传算法(GA)的逐时冷负荷预测模型,建模时以前一日已知的24小时室外干球温度为输入,以次日逐时冷负荷为输出.为提高预测精度及改善鲁棒性,以均方差(MSE)最小构造适应度函数,应用遗传算法寻优广义回归神经网络的平滑因子.通过预测负荷与实际负荷的比较分析验证了模型的可靠性和鲁棒性.     

Optimization Zone on the Performance of a Generalized Irreversible Magnetic Stirling Cryocooler

Finite time thermodynamic performance of a generalized irreversible magnetic Stirling cryocooler coupled to constant-temperature heat reservoirs has been analyzed in this paper. The relationship between the optimal cooling load and the coefficient of performance for the magnetic Stirling cryocooler is derived. The optimization zone on the performance of the cryocooler is obtained. The results obtained here will be useful for the further understanding and the selection of the optimal operating conditions for a magnetic Stirling cooler.     

中压配电网电力空间负荷密度分布仿真

针对传统方法没有考虑到同类负荷分布不均,导致无法为电力预测提供可靠的数据基础的问题,提出一种中压配电网应用电力空间负荷密度特性研究方法。按照中压配电网应用电力空间实际情况,通过元胞生成在应用电力空间中完成土地使用种类的模拟,利用GIS平台得到元胞的空间分布以及涉及属性数据,形成数据表。通过均匀核函数获取核密度计算的一般形式,采用核估计实现中压配电网应用电力空间负荷密度计算,解决负荷分布不均的问题,并确定中压配电网应用电力空间负荷密度及其置信区间。在此基础上运用Logistic曲线对负荷密度指标进行拟合,通过回归模型获取不同产业占比和负荷密度间的关系,得到差异分位数下负荷密度指标和各产业占比间的定量关系,获取负荷密度分布特性。分析实验结果得出,所提方法研究结果和实际结果基本一致,方法可靠。     

MongoDB负载均衡算法优化研究

随着Web2.0网络应用的兴起和大数据技术的发展,传统的关系型数据库(ORDBMS)已经难以满足海量数据的存储需求。非关系型数据库(NoSQL)因其高扩展性、高伸缩性、高可用性和容错性等特点,得到了越来越多的应用。作为一种新兴的NoSQL数据库,MongoDB数据库因具有模式自由、易于扩展、故障自动恢复、支持自动分片等特点,被广泛应用于大数据处理与分析中。文中首先介绍了MongoDB自动分片架构原理和实现机制,然后分析了MongoDB自带的负载均衡算法,其虽能使各个节点数据量达到平衡,但没有考虑各个节点的负载均衡。为了解决节点的负载平均问题,在原算法基础上提出了一种基于节点实时负载的负载均衡改进算法,改进算法的主要思想是引入节点负载指数作为chunk块迁移的一个判断条件。通过搭建测试环境并进行实验,验证了改进的负载均衡算法可以有效地均衡分片中的数据,提高集群的并发读写性能,从而证明了算法的有效性。     

The Performance Analysis of a Quantum Brayton Refrigeration Cycle with an Ideal Bose Gas

A Brayton refrigeration cycle using an ideal Bose gas as the working substance is simply referred to as a quantum Brayton refrigeration cycle, which consists of two constant-pressure and two adiabatic processes. The influence of quantum degeneracy on the performance of the cycle is investigated, based on the correction equation of state of an ideal Bose gas. The general expressions of the coefficient of performance, refrigeration load and work input of the cycle are calculated. The lowest temperature of the working substance and the minimum pressure ratio of the two constant-pressure processes for a quantum Brayton refrigeration cycle are determined. The variations of the relative refrigeration load with the temperature of the cooled space and the pressure of the low constant-pressure process are discussed for three special cases. Some curves related to the important performance parameters are given. The results obtained here are compared with those of a classical Brayton refrigeration cycle using an ideal gas as the working substance. Some significant conclusions are obtained.     

Co-evolution of Density and Topology in a Simple Model of City Formation

We study the influence that population density and the road network have on each others’ growth and evolution. We use a simple model of formation and evolution of city roads which reproduces the most important empirical features of street networks in cities. Within this framework, we explicitly introduce the topology of the road network and analyze how it evolves and interact with the evolution of population density. We show that accessibility issues -pushing individuals to get closer to high centrality nodes- lead to high density regions and the appearance of densely populated centers. In particular, this model reproduces the empirical fact that the density profile decreases exponentially from a core district. In this simplified model, the size of the core district depends on the relative importance of transportation and rent costs.     

Effect of Heat Transfer Law on the Ecological Optimization of a Generalized Irreversible Carnot Engine

The optimal ecological performance of a irreversible Carnot engine with the losses of heat-resistance, heat leak and internal irreversibility, in which the transfer between the working fluid and the heat reservoirs obeys a generalized heat transfer law Q ∝ δ(Tⁿ), is derived by taking an ecological optimization criterion as the objective, which consists of maximizing a function representing the best compromise between the power and entropy production rate of the heat engine. Some special examples are discusses. A numerical example is given to show the effects of heat transfer law, heat leakage and internal irreversibility on the optimal performance of the generalized irreversible heat engine. The results can provide some theoretical guidance for the designs of practical engine.     

Runtime Analysis of a Simple Ant Colony Optimization Algorithm

Ant Colony Optimization (ACO) has become quite popular in recent years. In contrast to many successful applications, the theoretical foundation of this randomized search heuristic is rather weak. Building up such a theory is demanded to understand how these heuristics work as well as to come up with better algorithms for certain problems. Up to now, only convergence results have been achieved showing that optimal solutions can be obtained in finite time. We present the first runtime analysis of an ACO algorithm, which transfers many rigorous results with respect to the runtime of a simple evolutionary algorithm to our algorithm. Moreover, we examine the choice of the evaporation factor, a crucial parameter in ACO algorithms, in detail. By deriving new lower bounds on the tails of sums of independent Poisson trials, we determine the effect of the evaporation factor almost completely and prove a phase transition from exponential to polynomial runtime. A preliminary version of this paper appeared in the Proceedings of the 17th International Symposium on Algorithms and Computation (ISAAC 2006), volume 4288 of LNCS, pp. 618–627, Springer. Financial support for C. Witt by the Deutsche Forschungsgemeinschaft (SFB) in terms of the Collaborative Research Center “Computational Intelligence” (SFB 531) is gratefully acknowledged.     

多金属硫化物切削仿真分析及载荷波动优化

针对深海多金属硫化物切削时螺旋滚筒载荷波动过大,影响滚筒寿命及生产效率等问题,对滚筒运动和受力进行了分析,利用MATLAB对螺旋滚筒切削硫化物过程进行仿真,研究螺旋滚筒结构和工作参数与滚筒切削头载荷波动性的关系,并利用MATLAB优化工具箱中的fmincon函数和内置interior-point算法,对滚筒的结构和系统参数进行了优化.仿真结果表明,滚筒结构和工作参数对载荷波动性影响较大,优化后的滚筒切削厚度和截距增大,转速和牵引速度减小,此时载荷波动性更为平缓,x,y,z三向的波动分别降低8.2％,11.8％,13.7％,并且三向受力也明显减小,提高了螺旋滚筒的工作稳定性,延长了滚筒的使用寿命,有效改进了滚筒的生产效率.     

一种资源负载均衡的Web集群启发式优化算法

Web集群系统需要同时使用系统各种资源来满足客户的请求 ,如何做到系统资源均衡分配的同时 ,使系统资源利用率最优是一个急需解决的问题 .针对目前 Web集群的应用现状与特性 ,提出了一种既能使资源负载均衡又能充分利用系统资源的启发式算法 ,它是对集合划分问题 (Set Partitioning Problem,SPP)和多选择多维背包问题(Multiple- Choice Multi- Dimension Knapsack Problem,MMKP)的扩展与优化 .该启发式算法能显著地降低资源最优分配中的计算复杂度 ,使其能满足实时调度的需要 ,模拟实验证实了该方法的有效性     

MW级风电系统的变桨距控制及载荷优化

针对风速的随机性及不确定性的特性,以及大型变速变桨风电机组(Variable Speed Variable Pitch Wind Turbine,VSVP)在桨距控制过程中,由于其大转动惯量造成发电机转速响应延迟的问题,提出了一种基于卡尔曼滤波算法的风轮气动转矩观测器,并将气动转矩与参考转矩偏差作为控制器输入以及时响应外界风速变化.针对变桨过程中普遍存在的塔架前后振动和传动链扭转振动问题,提出了通过在原有控制策略的基础上采用加速度反馈和阻尼滤波的方式得到附加桨距角和转矩,从而抑制振动的控制方式.利用Bladed编制了外部控制嚣对某2MW风力发电机组进行仿真,验证了该算法的可靠性,将所提出的控制策略应用于MW级风力发电机组,能够改善桨距控制的动态特性,并有效降低关键部位疲劳载荷.     

Simple Explanation of the No Free Lunch Theorem of Optimization

The No Free Lunch Theorem of Optimization (NFLT) is an impossibility theorem telling us that a general-purpose universal optimization strategy is impossible, and the only way one strategy can outperform another is if it is specialized to the structure of the specific problem under consideration. In this paper, a framework is presented for conceptualizing optimization problems that leads to useful insights and a simple explanation of the NFLT.     

数据挖掘在连铸二冷配水控制优化中的应用

根据实际连铸生产线的现状和使用要求,利用数据挖掘技术对连铸二冷动态配水模型的仿真、二冷制度以及水流密度与传热系数的换算进行优化,提高了自主开发动态配水模型的效率和水平.从最终所建模型的效果来看,在满足现场需要的同时,达到了对国外先进技术吸收消化的目的.     

基于传热反问题的微型燃料电池冷却通道优化

为了改善微型质子交换膜燃料电池冷却系统的综合性能,研究了燃料电池冷却通道几何形状的优化设计问题。针对传统冷却通道内流动阻力太大的现状,在综合考虑系统冷却能力和系统阻力的前提下,利用SIMPLER算法和共轭梯度法,求解冷却通道传热及流动过程的几何边界条件反问题,优化设计冷却通道的最优几何形状。讨论了冷却通道几何形状的初始猜测值,以及系统冷却能力和系统阻力权重之比等因素对冷却通道形状优化的影响。数值仿真结果表明,当流道入口流体流速及流道入口高度给定时,利用上述的传热学反问题的优化方法能够有效优化冷却通道的几何形状,明显改善了冷却系统的综合性能。优化结果可为微型燃料电池冷却通道的优化设计和工程制造提供理论依据。     

卫星载荷安装平台结构轻量优化与仿真分析

结构轻量化是目前航天器设计的发展趋势.以国内某高精度成像卫星有效载荷安装平台为对象,为了降低卫星平台的质量,同时满足其在复杂外热流环境下的热变形要求,分别采用拓扑优化与铺层优化两种方法对卫星安装平台进行轻量优化设计.在整星有限元热变形分析基础上,以载荷安装平台的质量最轻为目标,对结构进行优化设计,并对整星进行模态分析以验证设计方案的可靠性.两种优化方法均满足结构热变形设计要求,相比拓扑优化方法,铺层优化方法可以大幅降低安装平台质量,并且可行性高.     

中长期电力负荷预测相关影响因素优化选择

为了更好地反映各种相关因素对负荷的影响,采用人工神经网络进行中长期负荷预测.基于人工神经网络原理,设计了一个由输入层、隐含层和输出层组成的三层BP网络模型,利用神经网络高度非线性建模能力,选取国内生产总值、重工业生产总值、轻工业生产总值、农业生产总值、第一产业、第二产业和第三产业等七个因素作为神经网络的输入变量.采用排除法对这些输入变量进行优化选择,并对预测精度的影响进行了探讨.仿真结果证明利用排除法后预测精度明显提高,故提出的方法是可行和有效的.