基于改进Kriging代理模型的自适应序列优化算法在离心压缩机蜗壳设计中的应用

提出了一种基于改进Kriging代理模型的自适应序列优化算法,并利用Matlab软件开发相应的优化平台.采用该优化平台,针对某特定流量工况,以质量流量平均总压损失系数为目标变量对离心压缩机蜗壳系统模型进行气动优化设计,并对优化前后蜗壳模型进行对比计算,来验证优化结果在实际蜗壳系统中的适用性.结果表明:优化后蜗壳的总压损失系数小、静压恢复系数大,性能得到改善.     

离心式压缩机蜗壳优化设计

基于蜗壳一维气动设计理论,经过参数修正后,获得等内径的不对称圆形蜗壳结构。应用计算流体动力学专业软件NUMECA对流动十分复杂的蜗壳内部流场进行了三维粘性数值计算分析。根据蜗壳内部气流流动特性分析,合理设计并改进蜗壳结构,改进后离心式压缩机整级性能得到提高。     

圆形截面离心压缩机蜗壳内部三维流动的测量与分析

利用五孔探针对大尺度低速离心压缩机的圆形截面蜗壳内部三维流动进行了详细的测量,给出了蜗壳螺旋通道部分径向测量截面的通流速度分布以及通流速度、总压、静压沿径向与圆周方向的分布图,并与一维计算的流量进行了比较.结果表明,各截面测量得到的流量与一维计算的趋势相同,且随着角度的增大,计算与实验之间的差别逐渐减小;另外,本试验蜗壳内的流动是复杂的三维流动,蜗壳各径向截面的通流速度沿径向的分布与动量矩守恒规律有比较明显的差别,总压沿圆周方向变化不明显.     

离心压缩机三维叶片参数化气动优化研究

为提高离心压缩机气动性能,考虑二元叶轮优化多以构型参数为变量,不适用于变量间存在交互作用的三维叶片。以某三元叶轮为优化对象,考虑各变量间的交互作用,采用Bézier曲线加载叶片角,直接选取三维叶片型线为优化变量进行气动优化。结合CFD数值仿真、非线性映射能力较强的BP神经网络与全局寻优能力较强遗传算法,以提升等熵效率和压比为目标进行优化。结果表明：设计工况下,优化后的叶轮等熵效率同比提升1.9%,压比同比提升0.3。三维叶片中部向吸力面偏移,叶片尾缘向压力面偏转可同时提升叶轮的效率和压比。     

基于多目标遗传算法的生物质气化过程参数优化

生物质气化过程是一个复杂的多目标非线性过程。通过对气化过程的机理分析,针对麦秸和玉米秸这2种软质秸秆类生物质原料特性,建立了气化过程的优化目标函数。在此基础上,采用多目标遗传算法对该目标函数进行优化设计计算。计算结果表明,该目标函数对生物质气化过程参数优化具有良好效果,也验证了该算法对于全局优化以及解决复杂非线性问题的有效性。     

利用遗传算法进行离心压缩机整级优化设计

建立了离心压缩机整级的物理损失模型,编制用于离心压缩机整级性能参数优化的遗传算法程序,并对优化前后该离心压缩机整级性能进行了数值模拟分析,以证实损失模型的可靠性以及将CHC遗传算法引入离心压缩机级性能参数优化的可行性.结果表明:与优化前相比,优化后整级的性能得到了一定程度的提升,级内流动更加合理,消除了分离,减少了损失.     

基于改进多种群遗传算法的节能环保多目标优化模型

电力系统多目标经济负荷分配问题是个非线性、高维的复杂优化问题。提出基于交互式的改进多种群遗传算法,通过引入精英策略和移民策略的多种群遗传算法可以有效地克服标准遗传算法容易陷入局部最优解、易早熟的缺陷。针对文中提出的煤耗和排放2个目标函数,提出了基于目标满意度和总体协调度的交互式多目标处理方法,通过寻求向量空间内满足总体协调度的最短”欧氏距离”,来贴近决策者满意的理想值,解决了各目标函数之间最优解的相互冲突,达到协调好各个目标函数的目的,充分体现了决策者的意愿。试验算例表明,该算法能够有效地解决电力系统多目标经济负荷分配问题。     

离心压缩机防喘振控制方法的研究及应用

介绍了离心压缩机防喘振控制器所采用的防喘振控制方法，离心压缩机防喘振控制器的原理及功能和在高炉鼓风机上的应用。     

基于改进多目标遗传算法的小浪底水库优化调度研究

针对传统多目标遗传算法(NSGA-Ⅱ)在进化过程中存在的不足,首先利用拟随机Halton序列及自适应调整的方法对初始种群多样性和算法收敛性进行改进;然后选取小浪底水库为例,建立水库多目标优化调度模型,并运用改进的NSGA-Ⅱ算法对模型进行求解;最后采用模糊优选法对得到的Pareto最优解集进行方案优选。结果表明,改进的算法相比传统算法更为高效、合理,且调度结果符合客观实际。     

Computational and experimental study of an industrial centrifugal compressor volute

IntrotctionThe overall performance of a centrifugal compressoris a combination of the dueller, diffuser, and voluteperformances. Each component has to be designedcarefully in order tO' minimize the losses and maximizethe efficiency. In this paper, a centrifugal compressorvolute (or spiral) is stUdied numerically, and the CFDresults are compared with measured data.A volute is used to collect the flow from a vaned orvaneless diffuser and to gUide it Ollt of the compressor.The volute geometry…     

Novel multidisciplinary design and multi-objective optimization of centrifugal compressor used for hydrogen fuel cells

One-dimensional (1D) design and optimization of the impeller plays a significant role in performance improvement of the centrifugal compressor. However, most of the concentration has been paid to three-dimensional (3D) optimization of blades, few attention was focused on main control parameters determining aerodynamic performance and their optimal combination. Thus, this study innovatively developed a multidisciplinary design method combined with empirical 1D loss models, statistical analysis, and multi-optimization theory. The preliminary design of 1D parameters was developed based on empirical loss models. Besides, the analysis of variance of signal to noise ratio (SNR) was applied to find the main control parameters according to their contributions. To maximize the total pressure ratio and isentropic efficiency, the multi-objective optimization based on grey relational grade (GRG) was used to find the optimal combination of 1D parameters. The results showed that the impeller outlet width and impeller outlet radius are the most sensitive parameters affecting compressor performance. The optimal combination of 1D parameters is obtained. Compared to the initial design, the optimal impeller can reduce consumed power of 2.99%, enhance the isentropic efficiency of 1.24% at design point, and obtain the maximum increment of isentropic efficiency of 2.16% at 50 g/s operating point at 70,000 rpm.     

Centrifugal compressor blade optimization based on uniform design and genetic algorithms

An optimization approach to centrifugal compressor blade design, incorporating uniform design method (UDM), computational fluid dynamics (CFD) analysis technique, regression analysis method and genetic algorithms (GA), is presented. UDM is employed to generate the geometric information of trial samples whose performance is evaluated by CFD technique. Then, function approximation of sample information is performed by regression analysis method. Finally, global optimization of the approximative function is obtained by genetic algorithms. Taking maximum isentropic efficiency as objective function, this optimization approach has been applied to the optimum design of a certain centrifugal compressor blades. The results, compared with those of the original one, show that isentropic efficiency of the optimized impeller has been improved which indicates the effectiveness of the proposed optimization approach.     

Centrifugal compressor blade optimization based on uniform design and genetic algorithms

An optimization approach to centrifugal compressor blade design, incorporating uniform design method (UDM), computational fluid dynamics (CFD) analysis technique, regression analysis method and genetic algorithms (GA), is presented. UDM is employed to generate the geometric information of trial samples whose performance is evaluated by CFD technique. Then, function approximation of sample information is performed by regression analysis method. Finally, global optimization of the approximative function is obtained by genetic algorithms. Taking maximum isentropic efficiency as objective function, this optimization approach has been applied to the optimum design of a certain centrifugal compressor blades. The results, compared with those of the original one, show that isentropic efficiency of the optimized impeller has been improved which indicates the effectiveness of the proposed optimization approach. __________ Translated from Journal of Power Engineering, 2007, 27(5): 713–716 [译自: 动力工程]     

Configuration optimization of shell-and-tube heat exchangers with helical baffles using multi-objective genetic algorithm based on fluid-structure interaction

The configuration parameters of helical angle and overlapped degree of shell-and-tube heat exchangers with helical baffles have been discussed for the thermal-structural comprehensive performance. Based on fluid-structure interaction theory, a method on configuration optimization of shell-and-tube heat exchangers with helical baffles is introduced using second-order polynomial regression response surface combined with Multi-objective Genetic Algorithm. The results show that the heat transfer coefficient per unit pressure drop of shell-and-tube heat exchangers with helical baffles increases firstly and then decreases with the increase of helical angle, and decreases with the increase of overlapped degree under certain shell-inlet velocity. And the performance of flow and heat transfer is more sensitive to helical angle compared with overlapped degree. The maximum shear stress increases with helical angle, but it is almost unaffected by overlapped degree for mechanical properties of helical baffles. The objectives of optimization are the heat transfer coefficient per unit pressure drop maximizing and maximum shear stress minimizing with scope of allowable stress, and three optimal structures are obtained. The optimal results indicate that the heat transfer coefficient per unit pressure drop increases averagely by 14.1%, the maximum shear stress decreases averagely by 4.1%, which provides theoretical guidance for industrial design of shell-and-tube heat exchangers with helical baffles.     

Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm

Thermal modeling and optimal design of compact heat exchangers are presented in this paper. ε–NTU$\epsilon ''–''\mathit{NTU}$ method was applied to estimate the heat exchanger pressure drop and effectiveness. Fin pitch, fin height, fin offset length, cold stream flow length, no-flow length and hot stream flow length were considered as six design parameters. Fast and elitist non-dominated sorting genetic-algorithm (NSGA-II) was applied to obtain the maximum effectiveness and the minimum total annual cost (sum of investment and operation costs) as two objective functions. The results of optimal designs were a set of multiple optimum solutions, called ‘Pareto optimal solutions’. The sensitivity analysis of change in optimum effectiveness and total annual cost with change in design parameters of the plate fin heat exchanger was also performed and the results are reported. As a short cut for choosing the system optimal design parameters the correlations between two objectives and six decision variables with acceptable precision were presented using artificial neural network analysis.     

基于遗传算法的分布式发电优化

提出了一种用遗传算法来优化分布式发电的位置、数量和比例,从而提高电压质量减少网损的优化模型,并以一个28节点的配电网络为算例,在不考虑负荷增加与网络拓扑变化的情况下,给出了优化结果,并对结果进行了讨论。     

基于交互式多目标优化算法的风光互补发电系统优化

风光互补发电系统的优化配置是一个多目标优化问题,优化目标为系统安装成本,约束条件为供电可靠性。合理的匹配设计是充分发挥风光互补发电系统优越性的关键。在成本(目标)函数的最优化计算中,提出一种基于偏好的交互式多目标优化算法,利用交互式遗传算法优化目标权重值组成的种群,利用粒子群优化算法优化加权单目标函数,并将其应用到风光互补发电系统的优化配置中。计算结果表明,在满足负荷用电的前提下,风光互补发电系统的经济性能优于单独的光伏系统和风电系统。