水轮机空化声发射信号的优化VMD特征提取

针对变分模态分解(VMD)算法中分解层数和惩罚因子2个参数对分解结果有着显著影响且不易确定的问题,提出了灰狼和布谷鸟混合优化VMD算法(简称优化VMD算法).该方法以包络熵差异互相关系数作为适应度函数,以全局最小适应度值为优化目标,筛选出最佳的VMD参数组合.将优化VMD算法用于水轮机空化声发射信号的特征分析,通过分解...     

灌区渠首水库群优化调度模型及其求解

建立了梅院泥灌区渠首水库群优化调度的数学模型。针对该模型的特点,借鉴生物体的免疫原理,提出求解该问题的免疫遗传算法。该算法将局部最优解视为抗原,设计了对应的抗体产生机制。实例研究表明,该算法有效地抑制了早熟现象,具有良好的全局收敛性。     

基于连续蚁群算法的供水水库优化调度

针对供水水库优化调度问题,介绍了一种改进的连续蚁群算法。该算法借鉴蚁群算法的进化思想,主要包括局部搜索、全局搜索和信息素强度更新规则。在随机搜索过程中嵌入确定性搜索,以改善寻优性能,增加经验指导,从而加速收敛。将该算法与离散蚁群算法相比较,结果表明,该算法更优越,具有并行化和较强的全局寻优能力。     

基于改进粒子群算法的多目标无功优化

提出了一种基于粒子群算法的多目标优化方法,该算法采用Pareto支配关系来更新粒子的个体最优和全局最优值,用存储池保存搜索过程中发现的非支配解;采用聚类算法裁剪非支配解,以保持解的分散性;采用动态惯性权重来平衡粒子的局部和全局搜索能力,并将该算法应用于IEEE14节点系统的多目标无功优化。     

遗传算法在电控汽油机控制参数优化中的应用

在发动机电控系统的应用开发过程中，需要对电控系统中的控制参数进行优化。针对一定的测试规范进行控制参数的全局优化是一种先进的思想，目前国际上普遍采用Lagrange乘子法，但它具有不一定能获得全局最优解和有可能在求解过程中发生振荡或收敛缓慢等缺点。作提出了采用遗传算法求解控制参数全局优化问题，并且将该方法首次集成到研制的自动化标定系统中，指导控制参数在线优化进程，进行了1-4发动机配装SBEC-Ⅱ电控系统的基本控制参数优化工作。试验结果证实了采用遗传算法求解全局优化问题的优越性。     

基于遗传算法的动力总成悬置系统优化设计

动力总成作为工程机械的主要激励源,其悬置系统的设计水平直接影响到整机的隔振性能。以能量解耦率为目标函数的动力总成悬置系统优化设计是一个具有多个局部最优解的问题,因此需要运用全局搜索能量强的遗传算法进行求解。与采用传统优化算法相比,遗传算法可以求得全局最优解,并且可以设计出各自由度方向上均具有较高解耦率的方案。     

人工蜂群算法在电网储能系统管理中的运用北大核心CSCD

人工蜂群算法是一种全局搜索的优化算法,对于电网储能系统管理具有重要作用。该优化算法能够更加精准地控制和管理电网储能设备,以缜密的搜索计算得到问题最优答案,而后将其应用在储能系统设备中,保证电网储能系统的高效、稳定和协同运行,提升整体工作效率。本文探讨了人工蜂群算法对电网储能系统管理的作用,提出具体化的实践策略。     

基于能级概念的Yong经济学计价策略

正确合理地对Yong流计价，确定从燃料到产品Yong流的转换过程中费用形成及变化过程，是实现能量系统的炯经济学分析和优化的关键之一。将能级的概念引入热经济学计价体系。把供入能流按能级拆分，依据能级相近最大化相供的原则，解决能量取出与供入间的对应问题，提出了基于能级相近最大化相供的Yong流计价策略，以减少求解过程中所涉及的未知变量数。说明产品Yong流存在时的附加方程引入情况。最后以典型的热电联产系统(CGAM系统)的Yong经济分析优化中Yong流计价为例，介绍了该计价方法的应用。     

基于BP神经网络和分解技术的汽轮机叶片可靠性反求设计

汽轮机叶片可靠性反求设计旨在确定叶片未知概率设计参数以满足给定的可靠度要求.针对叶片功能函数为随机变量隐性函数的情况,提出了基于有限元、BP神经网络和分解技术的可靠性反求设计方法,该方法将有限元和BP神经网络相结合以构造功能函数与随机输入变量之间的近似解析表达式,运用分解技术,将求解随机设计参数的全局优化问题分解为主问题和子问题,通过子问题直接调用标准优化工具箱得到可靠性指标,并运用分解迭代技术对主问题求解,从而得到随机设计参数及目标可靠性指标对各随机变量的敏感性.以某实验台汽轮机等直叶片为例,阐述了该方法的具体实施过程.该方法数学描述简单,并可直接应用标准优化程序,成功地解决了隐性功能函数下叶片可靠性反求设计,具有较好的工程应用价值.     

改进的混沌优化方法在电站机组负荷分配中的应用

利用搜索过程中的先验知识，提出了一种改进的变尺度混沌优化算法，对电厂机组负荷分配这一类高维、非线性问题进行寻优。该算法利用混沌运动的遍历性和随机性进行全局搜索，结合下降法思想在当前最优解的局部空间搜索，提高算法的收敛速度。通过罚函数，将非线性约束问题转化为非约束问题求解，在寻优操作过程中检验解的有效性。并采用目标函数中负荷取值区间判别方法，降低优化问题的规模，减少了计算次数。与传统遗传算法相比，改进的混沌优化算法获得了更好的效果。     

基于多目标优化的配电网负荷转移路径研究

建立了配电网故障后负荷转移路径优化模型,提出了优化的目标函数和约束条件。应用带精英策略的快速非支配排序遗传算法（NSGA-Ⅱ）求解该多目标多约束优化问题,得到的最优解集能更好地反映优化问题的本质,并结合熵权法建立了综合最优解的提取方法。根据提出的算法,编制了应用于配电网负荷转移的程序,用IEEE33节点算例验证了该算法的可行性。     

增强输电能力的TCSC选址与定容研究

提出了一种新的TCSC选址方法,采用简易粒子群算法求出系统中较为敏感的支路群,用改进的粒子群算法在较敏感支路群中确定TCSC的最佳安装位置,并求出TCSC的最佳安装个数和安装容量,来达到系统输电能力最大的目的。针对PSO易陷入局部最优的缺陷,把种群熵的概念引入粒子群算法对其进行了改进．IEEE30节点系统的仿真计算结果验证了所提方法的有效性。     

Equipartition of entropy production as an approximation to the state of minimum entropy production in diabatic distillation

We show that the theorem of equipartition of entropy production is important for the understanding of the state of minimum entropy production in diabatic distillation. The theorem is not valid in a strictly mathematical sense. We explain why, when and in what sense this theorem is a good approximation to the optimal state in diabatic distillation. In order to make these predictions, we use a hypothesis for the state of minimum entropy production of an optimally controlled system, which was formulated on the basis of results of entropy production minimisation in chemical reactors. The hypothesis says that the state of minimum entropy production is characterised by approximately constant local entropy production and thermodynamic forces, given that there is sufficient freedom in the system. We present numerical results which are in agreement with the predictions. The results show that a column with constant tray entropy production in the stripping section and in the rectifying section is a good approximation to the optimal column, except when the total heat transfer area is low. The agreement between the two columns becomes better and better as the total heat transfer area and the number of trays increase. The fact that the predictions and the numerical results agree very well gives support to the validity of the hypothesis.     

系统参数对超临界水冷堆子通道熵产影响分析

利用流体力学计算软件CFX,采用结构化网格,研究系统参数如系统压力、热流密度以及质量流率对超临界水冷堆堆芯子通道内熵产行为的影响。湍流模型选择SSG雷诺应力模型,近壁面采用加强壁面处理方法。研究结果表明:系统压力对子通道熵产的影响有限,而热流密度和质量流率的影响则更为显著。随着热流密度的升高,传热对熵产的贡献增大,子通道内主流熵产增加;随着质量流率的升高,流体摩擦阻力对熵产的贡献增大,子通道内主流熵产减少。为了从热力学角度综合评估系统参数对主流熵产行为的影响,引入无量纲熵产数,进一步获得合理的热流密度和质量流率的系统参数设计方案,为超临界水冷反应堆的概念设计提供一定的理论指导。     

Multi-Objective Design Optimization of Hollow Fiber Membrane-Based Liquid Desiccant Module Using Particle Swarm Optimization Algorithm

ABSTRACT

Hollow fiber membrane-based liquid desiccant air dehumidification is an effective method for air dehumidification. The benefit of this technique is that the carryover problem of air mixing with desiccant solution can be avoided. Optimal design of the hollow fiber membrane-based liquid desiccant module is presented in this paper. Two objective functions are total entropy generation and total annual cost. However, a lower entropy generation often corresponds to a higher cost of the designed hollow fiber membrane module. To balance the total entropy generation and the total annual cost of hollow fiber membrane-based liquid desiccant modules, the multi-objective particle swarm algorithm is developed for the optimal hollow fiber membrane module design problem. The geometric variables like length of fiber, inner diameter of fiber, number of fiber and packing fraction effect on the total entropy generation and total annual cost are studied. The optimal structural parameters of a hollow fiber membrane-based desiccant module are obtained using multi-objective particle swarm algorithm.     

A numerical investigation of entropy generation in the entrance region of curved pipes at constant wall temperature

In this study, developing incompressible viscous flow and heat transfer in the curved pipes are studied numerically to analyze the entropy generation and thermodynamic optimization in the entrance region at a constant wall temperature. The governing equations including continuity, momentum and energy equations are solved using a second order finite difference method based on the projection algorithm. Entropy generation and optimal Reynolds number calculation based on the entropy generation minimization are carried out for two cases considering the two groups of non-dimensional parameters both numerically and analytically. The comparison of the numerical results in the entrance region with the analytical ones in the fully developed region indicates that both solutions predict nearly the same optimal Reynolds numbers, specially, for the first group of the non-dimensional parameters.     

Novel and optimal integration of SOFC-ICGT hybrid cycle: Energy analysis and entropy generation minimization

Integrating fuel cells with conventional gas turbine based power plant yields higher efficiency, especially solid oxide fuel cell (SOFC) with gas turbine (GT). SOFCs are energy efficient devices, performance of which are not limited to Carnot efficiency and considered as most promising candidate for thermal integration with Brayton cycle. In this paper, a novel and optimal thermal integration of SOFC with intercooled-recuperated gas turbine has been presented. A thermodynamic model of a proposed hybrid cycle has been detailed along with a novelty of adoption of blade cooled gas turbine model. On the basis of 1st and 2nd law of thermodynamics, parametric analysis has been carried out, in which impact of turbine inlet temperature and compression ratio has been observed on various output parameters such as hybrid efficiency, hybrid plant specific work, mass of blade coolant requirement and entropy generation rate. For optimizing the system performance, entropy minimization has been carried out, for which a constraint based algorithm has been developed. The result shows that entropy generation of a proposed hybrid cycle first increases and then decreases, as the turbine inlet temperature of the cycle increases. Furthermore, a unique performance map has also been plotted for proposed hybrid cycle, which can be utilized by power plant designer. An optimal efficiency of 74.13% can be achieved at TIT of 1800 K and r_p,c 20.     

A distributed parameter model and its application in optimizing the plate-fin heat exchanger based on the minimum entropy generation

A general three-dimensional distributed parameter model (DPM) was developed for designing the plate-fin heat exchanger (PFHE). The proposed model, which allows for the varying local fluid thermophysical properties inside the flow path, can be applied for both dry and wet working conditions by using the uniform enthalpy equations. The grids in the DPM were generated to match closely the flow passage of the heat exchanger. The classical correlations of the heat transfer and the flow friction were adopted to avoid solving the differential equations. Consequently, the computation burden of DPM becomes significantly less than that of the Computational Fluid Dynamics method. The optimal design of a PFHE based on the DPM was performed with the entropy generation minimization taken into consideration. The genetic algorithm was employed to conduct the optimization due to its robustness in dealing with complicated problems. The fin type and fin geometry were selected optimally from a customized fin database. The PFHE included in an environmental control system was designed by using the proposed approach in this study. The cooling performance of the optimal PFHE under both dry and wet conditions was then evaluated.     

Minimizing the entropy production in heat exchange

We present a theoretical proof that the entropy production due to heat exchange in a heat exchanger is minimum when the local entropy production is constant in all parts of the system. The solution for the minimum is independent of the value of the heat transfer coefficient. The general case is compared to the minimization problem that has equipartition of forces as solution. It is found that equipartition of forces predicts the minimum from the general solution well for typical heat exchange conditions. The discrepancy between the two solutions depends largely on the temperature dependency of the heat transfer coefficient. The optimal heat exchange conditions are very well approximated in practice with a counter-current heat exchanger; since the minimum in the entropy production space probably is flat.     

Second law analysis for optimal thermal design of radial fin geometry by convection

This paper presents a second law analysis for the optimal geometry of fin array by forced convection. The analytical analysis involves the achievement of a balance between the entropy generation due to heat transfer and entropy generation due to fluid friction. In the design of a thermal system, it is important to minimize thermal irreversibilities because the optimal geometry will be found when the entropy generation rate is minimized. In this paper, the entropy generation rate is discussed and optimum thickness for fin array is determined on the basis of entropy generation minimization subjected to the global constraint. In addition, the influence of cost parameters on the optimum thickness of fin array is also considered and presented in graphical form. It has been found that the increase in cross flow fluid velocity will enhance the heat transfer rate that will reduce the heat transfer irreversibility.