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.     

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.     

Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm

In this study, a new shell and tube heat exchanger optimization design approach is developed. Artificial Bee Colony (ABC) has been applied to minimize the total cost of the equipment including capital investment and the sum of discounted annual energy expenditures related to pumping of shell and tube heat exchanger by varying various design variables such as tube length, tube outer diameter, pitch size, baffle spacing, etc. Finally, the results are compared to those obtained by literature approaches. The obtained results indicate that Artificial Bee Colony (ABC) algorithm can be successfully applied for optimal design of shell and tube heat exchangers.     

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.     

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.     

Optimization design of shell-and-tube heat exchanger by entropy generation minimization and genetic algorithm

In the present work, a new shell-and-tube heat exchanger optimization design approach is developed, wherein the dimensionless entropy generation rate obtained by scaling the entropy generation on the ratio of the heat transfer rate to the inlet temperature of cold fluid is employed as the objective function, some geometrical parameters of the shell-and-tube heat exchanger are taken as the design variables and the genetic algorithm is applied to solve the associated optimization problem. It is shown that for the case that the heat duty is given, not only can the optimization design increase the heat exchanger effectiveness significantly, but also decrease the pumping power dramatically. In the case that the heat transfer area is fixed, the benefit from the increase of the heat exchanger effectiveness is much more than the increasing cost of the pumping power.     

Exergetic optimization of shell and tube heat exchangers using a genetic based algorithm

In the computer-based optimization, many thousands of alternative shell and tube heat exchangers may be examined by varying the high number of exchanger parameters such as tube length, tube outer diameter, pitch size, layout angle, baffle space ratio, number of tube side passes.In the present study, a genetic based algorithm was developed, programmed, and applied to estimate the optimum values of discrete and continuous variables of the MINLP (mixed integer nonlinear programming) test problems. The results of the test problems show that the genetic based algorithm programmed can estimate the acceptable values of continuous variables and optimum values of integer variables. Finally the genetic based algorithm was extended to make parametric studies and to find optimum configuration of heat exchangers by minimizing the sum of the annual capital cost and exergetic cost of the shell and tube heat exchangers. The results of the example problems show that the proposed algorithm is applicable to find optimum and near optimum alternatives of the shell and tube heat exchanger configurations.     

Multi-objective optimization of shell and tube heat exchangers

The effectiveness and cost are two important parameters in heat exchanger design. The total cost includes the capital investment for equipment (heat exchanger surface area) and operating cost (for energy expenditures related to pumping). Tube arrangement, tube diameter, tube pitch ratio, tube length, tube number, baffle spacing ratio as well as baffle cut ratio were considered as seven design parameters. For optimal design of a shell and tube heat exchanger, it was first thermally modeled using ε–NTU method while Bell–Delaware procedure was applied to estimate its shell side heat transfer coefficient and pressure drop. Fast and elitist non-dominated sorting genetic algorithm (NSGA-II) with continuous and discrete variables were applied to obtain the maximum effectiveness (heat recovery) and the minimum total cost 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 cost with change in design parameters of the shell and tube heat exchanger was also performed and the results are reported.     

Different Strategies to Improve Industrial Heat Exchange

A variety of different strategies are available to process and equipment designers to improve industrial heat transfer. These range from the use of efficient forms of individual heat exchangers to the optimum utilization of the individual units in a network, generally referred to as "process integration." This article attempts to review these strategies with reference to the conventional and more recent forms of shell-and-tube heat exchangers. In the context of a heat exchanger network, process heat transfer intensification ( global intensification ), i.e., network design for maximum energy recovery, is a first important step. This needs to be then combined with heat transfer intensification in individual units/shells ( local intensification ). The benefits of global and local intensification are illustrated with examples of a helically baffled heat exchanger ( Helixchanger ), as a representative of a more recent form of shell-and-tube exchanger. Some aspects concerning the use of multistream heat exchangers are discussed, and finally, an example for optimization of a plate-type heat exchanger is presented.     

Synthesis of Cost-Optimal Shell-and-Tube Heat Exchangers

Abstract

Synthesis of cost-optimal shell-and-tube heat exchangers is a difficult task since it involves a large number of parameters. An attempt is made in this article to simplify the process of choosing the parameter values that will minimize the cost of any heat exchanger satisfying a given heat duty and a particular set of constraints. The simplification is based on decoupling of the geometric and the thermal aspects of the problem. The concept of curves for cost-optimal design is introduced and is shown to simplify the synthesis process for shell-and-tube heat exchangers.     

管壳式换热器折流部件优化研究进展

为了提高管壳式换热器的能源利用率,换热器强化传热的研究得到广泛关注。本文从强化传热原理、结构改进和设计优化等三方面对换热器折流部件的优化改进研究进行了分析和总结。其中,强化传热原理主要包括不同折流板通过改变流场的特性影响换热器性能;结构改进包括分段挡板、折流孔板和螺旋挡板的优化进展以及与单弓挡板的对比研究;设计优化包括利用各种新型算法对换热器结构参数的优化和成本的控制。针对管壳式换热器折流部件的强化传热问题,提出了非连续螺旋挡板的研究和结合多目标优化设计的结构改进是未来的重点研究方向。     

Heat exchanger optimization for geothermal district heating systems: A fuel saving approach

One of the most commonly used heating devices in geothermal systems is the heat exchanger. The output conditions of heat exchangers are based on several parameters. The heat transfer area is one of the most important parameters for heat exchangers in terms of economics. Although there are a lot of methods to optimize heat exchangers, the method described here is a fairly easy approach. In this paper, a counter flow heat exchanger of geothermal district heating system is considered and optimum design values, which provide maximum annual net profit, for the considered heating system are found according to fuel savings. Performance of the heat exchanger is also calculated. In the analysis, since some values are affected by local conditions, Turkey's conditions are considered.     

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.     

改进粒子群算法在管壳式换热器优化设计中的应用

以管壳式换热器每年的总费用作为目标函数,采用含随机扰动算子的改进粒子群算法(IPOS)对其进行了优化.在优化设计模型中,采用Bell-Delaware法描述壳侧流体,优化变量选择管程数、换热管内径和外径及间距、管布置方式、封头类型、流体分配方式、密封条数、壳程压降和管程压降.对采用IPOS算法得到的优化结果与相关文献的结果进行了比较.结果表明:IPOS算法具有全局收敛、计算精度高、稳定性好的特点,并能获得约束条件下管壳式换热器的最优设计方案.     

An approach for the optimum design of heat exchangers

In this paper, an approach for the optimum design of heat exchangers has been presented. Traditional design method of heat exchangers involves many trials in order to meet design specifications. This can be avoided through the present design method, which takes the minimization of annual total cost as a design objective. In alternative optimum design methods, such as Lagrange multiplier method, by changing one variable at a time and using a trial–error or a graphical method, optimum results are obtained in a long time. In the present design optimization problem, the total annual cost has been taken as the objective function and heat balance, and rate equation have been taken as equal constraint. The method using the penalty function transforms the constrained problem into a single unconstrained problem. To solve the optimal problem, the method of steepest descent has been used. Initial design variables include the tube‐inside coefficient of heat transfer, tube‐outside coefficient of heat transfer, temperature difference and outside tube area of heat transfer. The changes in variables are considered simultaneously to reach an optimum solution. The results show that the present approach is a powerful tool for optimum design of heat exchangers and is expected to be beneficial to energy industry. Copyright © 2004 John Wiley & Sons, Ltd.     

Application of intensified heat transfer for the retrofit of heat exchanger network

A number of design methods have been proposed for the retrofit of heat exchanger networks (HEN) during the last three decades. Although considerable potential for energy savings can be identified from conventional retrofit approaches, the proposed solutions have rarely been adopted in practice, due to significant topology modifications required and resulting engineering complexities during implementation. The intensification of heat transfer for conventional shell-and-tube heat exchangers can eliminate the difficulties of implementing retrofit in HEN which are commonly restricted by topology, safety and maintenance constraints, and includes high capital costs for replacing equipment and pipelines. This paper presents a novel design approach to solve HEN retrofit problems based on heat transfer enhancement. A mathematical model has been developed to evaluate shell-and-tube heat exchanger performances, with which heat-transfer coefficients and pressure drops for both fluids in tube and shell sides are obtained. The developed models have been compared with the Bell-Delaware, simplified Tinker and Wills-Johnston methods and tested with the HTRI® and HEXTRAN® software packages. This demonstrates that the new model is much simpler but can give reliable results in most cases. For the debottlenecking of HEN, four heuristic rules are proposed to identify the most appropriate heat exchangers requiring heat transfer enhancements in the HEN. The application of this new design approach allows a significant improvement in energy recovery without fundamental structural modifications to the network.     

An optimization study on the finned tube heat exchanger used in hydride hydrogen storage system – analytical method and numerical simulation

Metal hydrides show great potential for hydrogen storage. However, for efficient hydrogen storage, thermal management is the technical barrier. Among the different heat exchangers proposed in the literature, finned tube heat exchangers are of great technological interest due to their adaptability to wide range of practical applications, high compactness and high heat transfer efficiency. In the present paper, the optimization of finned heat exchanger considering both enhanced heat transfer and vessel volume efficiency is conducted. A semi-analytical expression of heat transfer rate from a single fin is derived. The effects of fin dimension (fin thickness and radius) on the heat exchanger performance are studied. It was shown that the thermal resistance of the whole heat exchanger can be reduced by increasing the fin radius and decreasing the fin thickness, while the fin volume is kept fixed. In the second part of the study, a 2-D numerical simulation was performed in order to validate the results of the analytical study. The effects of two parameters (cooling tube diameter, the fin length) on the hydrogen charging time were highlighted. The increasing in the tube diameter from 2.5 mm to 5 mm results to 25% reduction of the charging time, which is very noticeable. On the other hand, given a reactor radius, increasing the length of fin reduces the overall thermal resistance of the reactor-heat exchanger. The results showed that the decreasing of the thermal resistance of 13% leads to a decreasing in charging time of 42%. Finally, it was found that the results of the numerical simulation agreed qualitatively with those of analytical study. Therefore, the analytical solution presented can be used for a quick assessment of the finned tube heat exchanger design without significant errors.     

A robust learning based evolutionary approach for thermal-economic optimization of compact heat exchangers

This paper presents a robust, efficient and parameter-setting-free evolutionary approach for the optimal design of compact heat exchangers. A learning automata based particle swarm optimization (LAPSO) is developed for optimization task. Seven design parameters, including discreet and continuous ones, are considered as optimization variables. To make the constraint handling straightforward, a self-adaptive penalty function method is employed. The efficiency and the accuracy of the proposed method are demonstrated through two illustrative examples that include three objectives, namely minimum total annual cost, minimum weight and minimum number of entropy generation units. Numerical results indicate that the presented approach generates the optimum configuration with higher accuracy and a higher success rate when compared with genetic algorithms (GAs) and particle swarm optimization (PSO).     

Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm

This study explores the use of global sensitivity analysis (GSA) and harmony search algorithm (HSA) for design optimization of shell and tube heat exchangers (STHXs) from the economic viewpoint. To reduce the size of the optimization problem, non-influential geometrical parameters which have the least effect on total cost of STHXs are identified using GSA. The HSA which is a meta-heuristic based algorithm is then applied to optimize the influential geometrical parameters. To demonstrate the effectiveness and accuracy of the proposed algorithm, an illustrative example is studied. Comparing the HSA results with those obtained using genetic algorithm (GA) reveals that the HSA can converge to optimum solution with higher accuracy.