Mathematical Modeling and Multi-Objective Optimization of a Mini-Channel Heat Exchanger Via Genetic Algorithm

Selleri, Tommaso; Najafi, Behzad; Rinaldi, Fabio; Colombo, G.

doi:10.1115/1.4023893

Cited by 33 publications

(14 citation statements)

References 24 publications

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“…An optimal rib width is obtained for a given pitch width by changing rib width to achieve the maximum cell current density [47]. Our previous study demonstrated that the optimal rib width is only sensitive to the rib-electrode contact resistance and pitch width [19,21].…”

Section: Expressions For the Optimal Rib Widthsmentioning

confidence: 99%

Optimization of the Interconnect Ribs for a Cathode-Supported Solid Oxide Fuel Cell

et al. 2014

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A comprehensive mathematical model of the performance of the cathode-supported solid oxide fuel cell (SOFC) with syngas fuel is presented. The model couples the intricate interdependency between the ionic conduction, electronic conduction, gas transport, the electrochemical reaction processes in the functional layers and on the electrode/electrolyte interfaces, methane steam reforming (MSR) and the water gas shift reaction (WGSR). The validity of the mathematical model is demonstrated by the excellent agreement between the numerical and experimental I-V curves. The effect of anode rib width and cathode rib width on gas diffusion and cell performance is examined. The results show conclusively that the cell performance is strongly influenced by the rib width. Furthermore, the anode optimal rib width is smaller than that for cathode, which is contrary to anode-supported SOFC. Finally, the formulae for the anode and cathode optimal rib width are given, which provide an easy to use guidance for the broad SOFC engineering community.

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Section: Expressions For the Optimal Rib Widthsmentioning

confidence: 99%

Optimization of the Interconnect Ribs for a Cathode-Supported Solid Oxide Fuel Cell

et al. 2014

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“…It is found as the result of the MCDM problem that a set of alternatives which are A (10) , A (9) , and A (8) was found as the best choices. This implies that A (10) , A (9) , and A (8) have no superiority over another and therefore one of them can be regarded as optimum solution. These alternatives are highlighted in Table 1.…”

Section: Multiple-criteria Decision-making (Mcdm)mentioning

confidence: 99%

“…Finally, they concluded that entropy generation and maximum temperature of mini-channel heat sink have the same effect on optimization results, and there is not a unique optimum. Selleri et al [10] obtained a mathematical model for a mini-channel heat exchanger under laminar flow conditions using the analytical and numerical results available in the literature aiming to find optimal mini-channel exchanger design for various operating conditions. Then, they validated these mathematical models and used them for optimization problem definition.…”

Section: Introductionmentioning

confidence: 99%

Mini-channel heat exchanger optimization using genetic algorithm and multiple-criteria decision making

Subasi

2022

Journal of Thermal Engineering

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This study aims to apply an integrated optimization approach that combines Multi-objective Optimization (MOO) and Multiple-criteria Decision-making (MCDM) to optimize a multiport mini-channel having 2D sawtooth micro fins under laminar, transitional, and turbulent flow conditions. Water was considered as working fluid. The Reynolds number (Re), fin height (H f ), fin width (W f ), the number of micro-fins in each mini-channel (N), and the distance between the successive fins (S1) were selected as design and flow parameters and the Nusselt number (Nu) and the Poiseuille number (Po) were selected as objective functions. A Genetic Algorithm based MOO study was conducted using the correlations available in the literature aiming to find the optimum values of design and flow parameters that maximize Nu and minimize Po. Then, the VIsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method was employed to help designers to select an optimum design among the Pareto optimal solution set which is the output of MOO. Finally, the optimization results obtained were compared with those obtained by the 1st Law of Thermodynamics based Performance Evaluation Criteria (PEC). The advantages and disadvantages of these methods were discussed in detail. It is revealed that the integrated approach is a more comprehensive and flexible approach that also covers the results of PEC.

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“…Vividly, a perfect solution which can satisfy all of the objectives at the same time, does not exist. Therefore, a logical alternative for dealing with a multi-objective problem is to determine a set of solutions, each of which satisfies the objectives at a suitable level while not being dominated by any other solution [19]. In case all of the objective functions should be minimized, a feasible solution x is said to dominate another feasible solution y , if and only if , for i = 1,…,K and for least one objective function j.…”

Section: Humidifier Finite Difference Equationsmentioning

confidence: 99%

“…A solution is called Pareto optimal if it is not dominated by any other solution in the considered space [19]. Evolutionary algorithms, specifically genetic algorithm (GA), with their unique capabilities for this kind of problems, are promising methodologies for dealing with multiobjective optimization problems [19][20].…”

Section: Humidifier Finite Difference Equationsmentioning

confidence: 99%

Multi-objective Optimization of a Solar Humidification Dehumidification Desalination Unit

Rafigh

Mirzaeian

Najafi

et al. 2017

J. Phys.: Conf. Ser.

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Abstract. In the present paper, a humidification-dehumidification desalination unit integrated with solar system is considered. In the first step mathematical model of the whole plant is represented. Next, taking into account the logical constraints, the performance of the system is optimized. On one hand it is desired to have higher energetic efficiency, while on the other hand, higher efficiency results in an increment in the required area for each subsystem which consequently leads to an increase in the total cost of the plant. In the present work, the optimum solution is achieved when the specific energy of the solar heater and also the areas of humidifier and dehumidifier are minimized. Due to the fact that considered objective functions are in conflict, conventional optimization methods are not applicable. Hence, multi objective optimization using genetic algorithm which is an efficient tool for dealing with problems with conflicting objectives has been utilized and a set of optimal solutions called Pareto front each of which is a tradeoff between the mentioned objectives is generated. IntroductionWater demand already exceeds supply in many parts of the world and as the world population continues to rise, so does the water demand. It is expected that by 2025, more than 60% of world's population will have water shortages [1]. Regarding the fact that seawater is one of the most convenient sources of water, desalination can be a practical solution to this concern. Desalination refers to a process which removes salt and other minerals from water resulting in having fresh water. The required energy for this purpose can be provided by different sources including refrigeration cycle [2], combined cogeneration cycle, heat pump [3] or solar system. Limitation of natural gases and oil in addition to their undesired effect on environment arises more interest in application of renewable sources of energy. Due to the fact that solar energy has a good consistency with climatic conditions in regions which need potable water, it can be considered as an appropriate source of energy. It is noteworthy that among the various desalination technologies in use, only those based on a thermal principle of operation must be considered in combination with solar ponds [4].Additionally, many of the remote arid areas need low capacity desalination systems, while conventional desalination methods such as MSF, MEE, VC and RO are suitable for large and medium capacity of fresh water production; therefore utilizing mentioned methods for small capacity systems is not economical. Humidification-dehumidification desalination is a suitable choice for production of fresh water when the demand is decentralized [5]. A significant advantage of the HD technology

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Mathematical Modeling and Multi-Objective Optimization of a Mini-Channel Heat Exchanger Via Genetic Algorithm

Cited by 33 publications

References 24 publications

Optimization of the Interconnect Ribs for a Cathode-Supported Solid Oxide Fuel Cell

Optimization of the Interconnect Ribs for a Cathode-Supported Solid Oxide Fuel Cell

Mini-channel heat exchanger optimization using genetic algorithm and multiple-criteria decision making

Multi-objective Optimization of a Solar Humidification Dehumidification Desalination Unit

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