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.     

换热网络优化设计的研究进展

换热网络优化是化工生产中常遇到的一类问题,综述了换热网络优化设计的三种基本方法,分别指出了夹点技术、数学规划法和炯经济分析法的基本原理、应用领域、优缺点及其在国内外的发展状况,并对其作了展望,注重更接近于工程实际的考虑。     

Heat exchanger networks retrofit with considering pressure drop by coupling genetic algorithm with LP (linear programming) and ILP (integer linear programming) methods

This research is trying to develop a new procedure for retrofit of HENs including pressure drop using genetic algorithm (GA) coupled with linear programming (LP) and integer linear programming (ILP) methods. The GA is used to produce structural modifications whereas continuous variables are handled using a converted NLP formulation for Maximum Energy Recovery (MER). The converted NLP consists of an LP for MER with adding a search loop to find the best minimum approach temperature and split ratios which are easier to solve.To prevent complexity and ensure optimum solution, the pressure drops of streams are calculated from the results of LP and then a modified ILP problem is solved to determine the maximum profit of retrofit of HENs. The motivation of the ILP is decision making for elimination or reuse of current exchangers and pumps and/or introducing new ones to the network. Results show that the proposed method often finds better solutions than those reported in the literature.     

蚁群算法在换热网络优化中的应用

提出将蚁群算法应用于换热网络优化中,按照相等的能量份额将各股热流体分解成能量集合,热流体能量通过换热器在与冷流体换热的过程中得到分配,换热器单元面积得到相应地调整．能量分配过程中换热网络得到优化,从而使年综合费用减少的换热器面积不断积累,最终形成了一个最优的换热网络结构．通过具体算例验证了该方法的可行性和有效性,最终优化的结果证明该方法具有较强的全局搜索能力,能够应用于复杂换热网络的优化问题中．     

基于压降二次分配的换热网络综合研究

在换热网络的综合过程中,依据单体换热设备的换热面积,进行压降约束的初步线性分配,根据单体换热设备的详细设计结果,按流体流动方向,对压降约束进行再次分配,并校核流股总压降是否在允许的范围内,给出了考虑压降分配前提下的换热器详细设计流程框图,算例结果表明,依此方法综合出的新的能量系统与现场能量系统相比节省换热面积30．87％,系统压降总和降低12．66％。     

改进精度的换热网络优化遗传算法

在换热网络分级超结构及其数学模型基础上,提出了改进精度的换热网络优化综合遗传算法,该算法采用三层优化结构,利用中间层修正换热系数和流体物性,在计算量上升不多的情况下,从本质上提高了换热网络优化过程中的精度。采用此方法对炼油厂常减压系统进行优化,得到了良好的效果。     

Application for pinch design of heat exchanger networks by use of a computer code employing an improved problem algorithm table

In this work, the methods used in pinch design were applied to a heat exchanger network with the aid of an improved problem algorithm table. This table enables one to compose composite and grand composite curves in a simplified way. A user friendly computer code entitled DarboTEK, compiled by using Visual Basic 3.0, was developed for the design of integrated heat exchanger networks and estimation of related capital costs. Based on the data obtained from the TÜPRA petroleum refinery at Izmit, a retrofit design of heat exchanger networks was accomplished using DarboTEK. An investment of $ 3,576,627 is needed which will be paid back in 1.69 years simply by energy conservation due to heat integration.     

Studies on the retrofit of heat exchanger network based on the hybrid genetic algorithm

The retrofit of heat exchanger networks (HENs) is an important branch of investigation for systematic heat integration. The studies on the economical and efficient retrofit techniques are very important for the high energy-consumption enterprises to save energy, protect environment and improve their market competitiveness. Because the retrofit of HEN is an optimization problem normally solved by a mixed integer nonlinear program (MINLP) which requires enormous solution space, it is very difficult to solve it with the traditional optimization methods. In this paper, by the analysis of an existing heat exchanger network, the hybrid genetic algorithm is applied to obtain the optimal retrofitted HEN with full utilization of the existing heat exchangers and structures. Two examples are taken to show the better effect of the retrofit method with the optimal new heat exchangers and re-piping cost and energy saving.     

管翅式换热器遗传算法优化

管翅式换热器作为一种高效的换热设备,提升其换热效率和降低投资成本显得至关重要.通过单目标遗传算法(GA)和多目标非支配排序遗传算法(NSGA-Ⅱ)对管翅式换热器进行优化设计,设置翅片高度、翅片间距、管长、横向管数和纵向管数5个自变量的合理设计范围,单目标优化选用换热器效率、压降熵产和最大收益3个目标函数,根据热力学第一...     

利用夹点技术优化蒸馏换热网络

介绍夹点技术设计的基本原理及设计原则,采用Aspen Hx-net软件,运用夹点技术对某炼油厂常压蒸馏装置换热网络进行优化分析,确定最优传热温差△Tmin、最小公用工程用量和夹点位置,并对换热网络进行了优化.装置运行情况表明,优化后的换热网络节能效果明显,装置投资回收期仅8个月.     

Multi‐objective genetic algorithm optimization of thermoelectric heat exchanger for waste heat recovery

A model is developed to simulate a cross‐flow heat exchanger, including fins, in the wall of which thermoelectric generators are sandwiched. Such a system could be used for waste heat recovery. The model is used to optimize the device based on several objective functions: total volume, total number of thermoelectric modules, power output, and pumping power. The design variables are the local distribution of modules and of current, the shape of the fins, and the division of the heat exchanger in sub‐channels. Pareto fronts are achieved with a multi‐objective genetic algorithm, and are presented here. The results show that the number of sub‐channels in the heat exchanger has a larger impact on the overall performance than the fin geometry for this particular problem. Also, the net power output is mostly correlated to the number of thermoelectric modules, and less to the heat exchanger volume. Various relations between the different competing objectives are shown and analyzed. Copyright © 2011 John Wiley & Sons, Ltd.     

Experimental study on the heat transfer enhancement of MWNT-water nanofluid in a shell and tube heat exchanger

Heat transfer enhancement of multi-walled carbon natube(MWNT)/water nanofluid in a horizontal shell and tube heat exchanger has been studied experimentally. Carbon nanotubes were synthesized by the use of catalytic chemical vapor deposition (CCVD) method over Co–Mo/MgO nanocatalyst. Obtained MWNTs were purified using a three stage method. COOH functional groups were inserted for making the nanotubes hydrophilic and increasing the stability of the nanofluid. The results indicate that heat transfer enhances in the presence of multi-walled nanotubes in comparison with the base fluid.     

Predicting the capacity of a heat exchanger by a thermal network method

In this paper a thermal network method using the effective specific heat model of a refrigerant with phase change is proposed for predicting the capacity of a plate‐fin and tube‐type heat exchanger. The effective specific heat model can attain an accurate result of a condenser's heat exchanging capacity when it has a small number of elements. By comparing calculated results with those of an experiment, it is found that the error in the condenser's calculated capacity is less than 1% when the range of subcool temperature is from 15 to 22 K at the outlet of refrigerant flow. © 2002 Scripta Technica, Heat Trans Asian Res, 31(2): 128–140, 2002; DOI 10.1002/htj.10021     

Optimization design of slotted fin by numerical simulation coupled with genetic algorithm

Using a novel method that couples genetic algorithm (GA) with numerical simulation, the geometric configuration for a two-dimensional slotted fin has been optimized in this paper. The objective of optimization is to maximize the heat transfer capacity of slotted fin, and minimize the pressure drop penalty of fluid flow through the fin. The key of this method is the fitness function of GA, which were (j/j₀)/(f/f₀) and j/j₀. In this complex multiparameter problem, the numerical simulation is a crucial step to calculate the Colburn factor j and friction factor f. The results showed that for two-dimensional slotted fin considered, the j factor is increased by 229.22%, the f factor is increased by 196.30%, and the j/f ratio was increased by 11.11% at Re = 500 based on optimal integrated performance (j/j₀)/(f/f₀); the j factor is increased by 479.08% at Re = 500 based on optimal heat exchange capacity j/j₀. The feasibility of optimal designs was verified by the field synergy principle.     

Minimizing shell‐and‐tube heat exchanger cost with genetic algorithms and considering maintenance

This paper presents a procedure for minimizing the cost of a shell‐and‐tube heat exchanger based on genetic algorithms (GA). The global cost includes the operating cost (pumping power) and the initial cost expressed in terms of annuities. Eleven design variables associated with shell‐and‐tube heat exchanger geometries are considered: tube pitch, tube layout patterns, number of tube passes, baffle spacing at the centre, baffle spacing at the inlet and outlet, baffle cut, tube‐to‐baffle diametrical clearance, shell‐to‐baffle diametrical clearance, tube bundle outer diameter, shell diameter, and tube outer diameter. Evaluations of the heat exchangers performances are based on an adapted version of the Bell–Delaware method. Pressure drops constraints are included in the procedure. Reliability and maintenance due to fouling are taken into account by restraining the coefficient of increase of surface into a given interval. Two case studies are presented. Results show that the procedure can properly and rapidly identify the optimal design for a specified heat transfer process. Copyright © 2006 John Wiley & Sons, Ltd.     

Using genetic algorithms for the determination of an heat transfer coefficient in three-phase inverse Stefan problem

In the paper, an example is presented of the application of a genetic algorithm to a design inverse Stefan problem. The problem consists in the reconstruction of the function which describes the heat transfer coefficient, where the positions of phase change moving interfaces are well-known. In numerical calculations, the Tikhonov regularization, a genetic algorithm and a generalized alternating phase truncation method were used. The featured examples of calculations show a very good approximation of the exact solution.     

RWCE算法控制参数动态更新促进换热网络结构进化策略

相较其他进化算法,强制进化随机游走（RWCE）算法能够始终保持较高的种群多样性,从而有效地跳出局部最优。然而,目前对于该算法进化过程中的控制参数如最大步长、最小换热量或换热面积以及接受差解概率的设置仍无严格定义,其取值方法和取值范围都将对结构进化的进度、换热单元生成和消去速度以及最终的换热单元数产生直接影响。根据换热单元数设定逐渐变化的控制参数,进行逐级优化尝试。引入logistic函数作为接受差解概率的取值策略,使最大步长和保留系数均随换热单元数线性变化,实现控制参数的动态更新从而促进换热网络结构进化。通过算例验证,该策略能提高RWCE算法优化换热网络的效率,可获得更理想的网络结构。     

Optimizing circuit parameters of the biohydrogen real-time power generating system by genetic algorithm

This study performs optimal estimation of circuit parameters for a biohydrogen real-time power generating system by using a penalty-function genetic algorithm (GA). Circuit parameters of this system change with operating temperature and current density; some circuit parameters are nonlinear. To elucidate the circuit characteristics of the whole system, this study uses penalty-function GA to optimally estimate circuit parameters using data from a V–I$V–I$ characteristic experiment on novel biohydrogen real-time power generating system. This study then solves the circuit characteristic by the estimated circuit parameters formulated utilizing Kirchhoff's law. Then, the estimated V–I$V–I$ characteristic is then compared with actual measurements to verify the feasibility of this novel approach. In the same manner, the capacitor parameter of the biohydrogen real-time power generating system can be estimated to identify the alternating current (AC) equivalent circuit for this system.     

An approximate integral model with an artificial neural network for heat exchangers

In order to improve predicting precision and increase computation speed of simulation for heat exchangers, a novel method is presented in this paper, whereby an approximate integral model is used to simplify the original distributed parameter model and an artificial neural network is combined to reflect the nonlinear relations. This model is applied in actual calculations of fin‐and‐tube condensers and high precision is achieved. Where the calculated outlet temperature of refrigerant and that of air, the average errors are both less than 0.2 °C. For the heat exchange of the condenser, the average error is less than 1 0.2 °C. For the heat exchange of the condenser, the average error is less than 1%. The calculation speed of the approximate integral model is two orders of magnitude faster than that of the distributed‐parameter model. © 2004 Wiley Periodicals, Inc. Heat Trans Asian Res, 33(3): 153–160, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/htj.20006     

Optimal location of three heat sources on the wall of a square cavity using genetic algorithms integrated with artificial neural networks

In this work, optimization of location of heat sources in a square enclosure with natural convection is performed to maximize the global conductance in the enclosure. For this study we have taken a square enclosure with three adiabatic walls, one isothermal wall opposing the wall having three heat sources. Numerical simulations are done by changing positions of heat sources for different Rayleigh numbers using Fluent 6.3(2d, double precision). And for some configurations maximum temperature inside the enclosure is noted. Optimization is done using genetic algorithms (GA) combined with artificial neural networks (ANN). An ANN is trained using the above data obtained from numerical solutions. The trained ANN will be the simulation tool, whenever required by the GA for optimization. It is shown that at high Rayleigh number the spacing between the heat sources should be zero for optimum heat transfer. Variation in optimum solution for unequal heat fluxes are also studied.