城市原生污水源热泵最优化研究

根据现有城市原生污水源热泵的投资和运行等经济和技术特点,以系统的费用年值为目标函数,系统的冬夏季蒸发温度、冷凝温度、污水换热器出水温度、污水取水系统的管径等为优化变量,建立了系统综合优化的数学模型.在满足系统供冷、供热的可靠运行的条件下,利用遗传算法理论,并使用Matlab7.1遗传算法工具箱对系统的运行参数及机组部件的设计参数进行了优化选择,实现了系统费用年值最小的目标.优化结果与传统设计结果相比费用年值节省约6%.     

换热器性能的火用经济评价

通过对换热器传热与流动过程的(火用)经济分析,提出了一项换热器性能(火用)的经济评价指标--单位传热量的总费用η,并对顺流、交叉流和逆流三种流型的换热器进行了(火用)经济分析和优化.本文的有关方法和结论可为工程上换热器的性能评价提供参考.     

城市原生污水换热器的能效分析

结垢是影响城市原生污水换热器热工性能的主要原因.以壳管式污水换热器为例,在分析了污垢对换热器性能影响的基础之上,提出了换热器由于传热温差和流动阻力引起的不可逆有效能损失的计算方法,以及污水换热器不可避免(火用)损失的定义及计算方法.分析结果为污水换热器的工程应用和科学研究提供了理论基础.     

换热器性能的经济评价

通过对换热器传热与流动过程的火用经济分析,提出了一项换热器性能的火用经济评价指标———单位传热量的总费用η,并对顺流、交叉流和逆流三种流型的换热器进行了火用经济分析和优化。本文的有关方法和结论可为工程上换热器的性能评价提供参考。     

非清洁水源热泵系统换热器除污方法研究

非清洁水源热泵系统中,污水换热器换热面的污染问题导致流动阻力增大,换热系数降低,已成为污水源热泵发展的主要技术障碍之一.本文分析了现存的几种在线物理清洗方法应用于污水换热器除垢的局限性,基于污水换热器污垢的特点,针对管壳式换热器提出了适合于污水换热器去污方法,即小水量强力轮替冲洗部分换热管工艺,介绍了强力自冲洗换热器结构和原理,分析了其经济可行性.     

应用遗传算法优化设计微型燃气轮机原表面换热器

提出将热力性能设计与遗传算法搜索过程相结合的方法.对适用于100 kW微型燃气轮机的人字形交错波纹板式原表面换热器进行结构优化,分别以重量最轻和换热紧凑度/重量最大作为目标函数,把换热器芯体外形尺寸和换热表面结构尺寸作为待寻求最佳值的优化变量进行优化.遗传算法程序采用二进制编码,锦标赛选择,均匀交叉和单点变异,并采用基...     

换热器性能的Yong经济评价

通过对换热器传热与流动过程的Ｙｏｎｇ经济分析,提出了一项换热器性能的Ｙｏｎｇ经济评价指标－－单位传热量的总费用η,并对顺流、交叉流和逆流三种流型的换热咕嘟 Ｙｏｎｇ经济分析和优化。本文的有关方法和结论可为工程上换热器的性能评价提供参考。     

城市污水换热器的方案对比与设计

污水换热器是城市污水源热泵系统中的关键设备。针对污水自身的特点,从工程角度总结了污水换热器必须满足的基本要求和特点;介绍并对比分析了几种常见的污水换热器形式,指出宽流道式换热器将带来阻力增大、能耗增加、投资增长,而壳管式换热器是最科学的污水换热器形式。给出了污水换热器设计的基本方程组,总结给出了工程设计中常见的4种技术条件组合下污水换热器的设计方法。本文提出的换热器结构、性能参数与流道尺寸的普适关系,以及污水换热器的设计方法对污水源热泵工程设计和运行具有指导意义。     

应用遗传算法优化设计管壳式换热器

两级管壳式换热器优化设计是一个有约束非线性规划问题,目前还没有方法能够保证寻找到该问题的全局最优解.传统的转动坐标轴直接搜索可行方向法(DSFD方法)可以获得该问题的局部最优解,但该最优解对初始点的依赖性很大,需要多次尝试寻找"全局"最优解.应用遗传算法对两级管壳式换热器进行优化设计,优化结果与DSFD方法优化结果对比表明,遗传算法更易于寻找"全局"最优解,提高优化过程的效率.     

污水源热泵系统污水水质与换热器材质的选择

讨论了污水源热泵系统污水水质的分类,提出了采用中水的污水源热泵系统的水质标准及处理方法,分析了各种污水换热器的特点及适用条件.在非金属类材料中,从经济性能、传热性能等方面综合分析,建议采用HDPE管和PE-X管作为污水换热器管材.     

Economic optimization of shell and tube heat exchanger based on constructal theory

In this paper, the new approach of constructal theory has been employed to design shell and tube heat exchangers. Constructal theory is a new method for optimal design in engineering applications. The purpose of this paper is optimization of shell and tube heat exchangers by reduction of total cost of the exchanger using the constructal theory. The total cost of the heat exchanger is the sum of operational costs and capital costs. The overall heat transfer coefficient of the shell and tube heat exchanger is increased by the use of constructal theory. Therefore, the capital cost required for making the heat transfer surface is reduced. Moreover, the operational energy costs involving pumping in order to overcome frictional pressure loss are minimized in this method. Genetic algorithm is used to optimize the objective function which is a mathematical model for the cost of the shell and tube heat exchanger and is based on constructal theory. The results of this research represent more than 50% reduction in costs of the heat exchanger.     

Applying multiple decomposition methods and optimization techniques for achieving optimal cost in mixed materials heat exchanger networks

The optimization of the total annual cost in heat exchanger networks has been one of the overarching goals when synthesizing these networks. Several methodologies and techniques have been developed to achieve optimal costs in mixed material heat exchanger networks. This paper demonstrates the application of two decomposition methodologies (total decomposition and partial decomposition) for typical cost rules. The objective function was defined as the optimization and minimization of the total annual cost in mixed materials heat exchanger network. Three optimization algorithms, hybrid genetic‐particle swarm optimization (GA‐PSO), shuffled frog leaping algorithm (SFLA) techniques, and ant colony optimization (ACO), were used to further optimize the total cost in mixed materials heat exchanger network. The results indicate that the total annual cost in partial decomposition method was smaller than that in full integration method and total decomposition method. The reduction of the total annual cost was about 27% for GA‐PSO algorithm, 24% for SFLA and 10% for ACO relative to the results reported in this work. In partial decomposition method, at least one mixed material of heat exchanger was used to reduce the hot and cold utility for decreasing the total annual cost. Partial decomposition method resulted in the highest reduction of the total annual cost compared with other methods. Percentage of difference of the total annual cost were 0.36%, 1.92%, and 5.05% for full integration, total decomposition, and partial decomposition methods, respectively, in comparison with the previous studies. Results have been compared with the results of other studies to demonstrate the accuracy of the applied algorithms.     

The application of field synergy number in shell-and-tube heat exchanger optimization design

In the present work the field synergy principle is applied to the optimization design of the shell-and-tube heat exchanger with segmental baffles. The field synergy number which is defined as the indicator of the synergy between the velocity field and the heat flow is taken as the objective function. The genetic algorithm is employed to solve the heat exchanger optimization problems with multiple design variables. The field synergy number maximization approach for heat exchanger optimization design is thus formulated. In comparison with the initial design, the optimal design leads to a significant cost cut on the one hand and an improvement of the heat exchanger performance on the other hand. The comparison with the traditional heat exchanger optimization design approach with the total cost as the objective function shows that the field synergy number maximization approach is more advantageous.     

Thermodynamic optimization of cross flow plate-fin heat exchanger using a particle swarm optimization algorithm

This study explores the use of particle swarm optimization (PSO) algorithm for thermodynamic optimization of a cross flow plate-fin heat exchanger. Minimization of total number of entropy generation units for specific heat duty requirement under given space restrictions, minimization of total volume, and minimization of total annual cost are considered as objective functions and are treated individually. Based on the applications, heat exchanger length, fin frequency, numbers of fin layers, lance length of fin, fin height and fin thickness or different flow length of the heat exchanger are considered for optimization. Heat duty requirement constraint is included in the procedure. Two application examples are also presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization using PSO are validated by comparing with those obtained by using genetic algorithm (GA). Parametric analysis is also carried out to demonstrate the effect of heat exchanger dimensions on the optimum solution. The effect of variation of PSO parameters on convergence and optimum value of the objective has also been presented.     

An imperialist competitive algorithm for optimal design of plate-fin heat exchangers

This paper presents the application of imperialist competitive algorithm (ICA) for optimization of a cross-flow plate fin heat exchanger. Minimization of total weight and total annual cost are considered as objectives. Seven design parameters, namely, heat exchanger length at hot and cold sides, fin height, fin frequency, fin thickness, fin-strip length and number of hot side layers are selected as optimization variables. A case study from literature is presented to show the effectiveness of the proposed algorithm. The numerical results reveal that ICA can find optimum configuration with higher accuracy in less computational time when compared to conventional genetic algorithm (GA).     

Optimal design of plate-fin heat exchangers by a hybrid evolutionary algorithm

This study explores the first application of a Genetic Algorithm hybrid with Particle Swarm Optimization (GAHPSO) for design optimization of a plate-fin heat exchanger. A total number of seven design parameters are considered as the optimization variables and the constraints are handled by penalty function method. The effectiveness and accuracy of the proposed algorithm is demonstrated through an illustrative example. Comparing the results with the corresponding results using GA and PSO reveals that the GAHPSO can converge to optimum solution with higher accuracy.     

Optimizing heat exchanger networks with genetic algorithms for designing each heat exchanger including condensers

This paper presents a procedure for the design of the components of a heat exchanger network (HEN). The procedure first uses pinch analysis to maximize heat recovery for a given minimum temperature difference. Using a genetic algorithm (GA), each exchanger of the network is designed in order to minimize its total annual cost. Eleven design variables related to the exchanger geometry are considered. For exchanger involving hot or cold utilities, mass flow rate of the utility fluid is also considered as a design variable. Partial or complete condensation of hot utility fluid (i.e., water vapor) is allowed. Purchase cost and operational cost are considered in the optimization of each exchanger. Combining every exchanger minimized cost with the cost of hot utility and cold utility gives the total cost of the HEN for a particular ΔT_min. The minimum temperature difference yielding the more economical heat exchanger network is chosen as the optimal solution. Two test cases are studied, for which we show the minimized total cost as a function of the minimum temperature difference. A comparison is also made between the optimal solution with the cost of utilities and without it.     

Exergetic Optimization of Shell-and-Tube Heat Exchangers Using NSGA-II

In this article, a multi-objective exergy-based optimization through a genetic algorithm method is conducted to study and improve the performance of shell-and-tube type heat recovery heat exchangers, by considering two key parameters, such as exergy efficiency and cost. The total cost includes the capital investment for equipment (heat exchanger surface area) and operating cost (energy expenditures related to pumping). The design parameters of this study are chosen as tube arrangement, tube diameters, tube pitch ratio, tube length, tube number, baffle spacing ratio, and baffle cut ratio. In addition, for optimal design of a shell-and-tube heat exchanger, the method and Bell–Delaware procedure are followed to estimate its pressure drop and heat transfer coefficient. A fast and elitist nondominated sorting genetic algorithm (NSGA-II) with continuous and discrete variables is applied to obtain maximum exergy efficiency with minimum exergy destruction and minimum total cost as two objective functions. The results of optimal designs are a set of multiple optimum solutions, called “Pareto optimal solutions.” The results clearly reveal the conflict between two objective functions and also any geometrical changes that increase the exergy efficiency (decrease the exergy destruction) lead to an increase in the total cost and vice versa. In addition, optimization of the heat exchanger based on exergy analysis revealed that irreversibility like pressure drop and high temperature differences between the hot and cold stream play a key role in exergy destruction. Therefore, increasing the component efficiency of a shell-and-tube heat exchanger increases the cost of heat exchanger. Finally, the sensitivity analysis of change in optimum exergy efficiency, exergy destruction, and total cost with change in decision variables of the shell-and-tube heat exchanger is also performed.     

基于温差均匀性因子协进化的双层算法同步优化换热网络

针对同时存在整型变量和连续型变量的换热网络综合问题,提出一种双层优化方法。外层以换热网络的温差均匀性因子作为网络结构性能的评价指标,通过蒙特卡洛随机抽样技术产生试探结构,采用整型优化算法逐步进化外层结构;内层以最小年综合费用作为优化指标,采用动态更新子群的改进粒子群算法优化连续变量。优化结果表明,温差均匀性因子可以有效评价换热网络的结构性能,从而指导结构的进化;改进的粒子群算法具有更强的全局搜索能力,相关算例均找到了更优的网络设计,应用于工业生产实际,可以有效节约成本。