Modeling and combined application of the modified NSGA-II and TOPSIS to optimize a refrigerant-to-air multi-pass louvered fin-and-flat tube condenser

Shojaeefard, Mohammad Hassan; Zare, Javad

doi:10.1016/j.applthermaleng.2016.04.093

“…In [15], the structures of microchannel heat sink with fan-shaped cavities and microchannel heat sink with triangular-shaped cavities were simulated and optimized, and it was concluded that the cavity action can destroy the microchannel flow and heat transfer boundary layer, thus enhancing the microchannel heat transfer. In [16], the effects of rib spacing ratio to pipe diameter (p/d), rib height ratio to pipe diameter (e/d), and Reynolds number on the flow and heat transfer in circular tubes with microchannels were experimentally studied, and the Nusselt (Nu) number and friction coefficient correlation equations with the three parameters of p/d, e/d, and Reynolds number as variables were proposed to guide engineering applications.…”

Section: Introductionmentioning

confidence: 99%

“…In [15], the flow and heat transfer in variable cross section and microchannel heat sink with rough elements were investigated, and two objective functions of thermal resistance and pumping power were optimized using a multiobjective genetic algorithm to obtain the Pareto optimization solution set. In [6], the multiobjective genetic algorithm was used to optimize the heat transfer coefficient and pressure drop for microchannels with concave structure using channel height, cavity spacing, and height as variables.…”

Section: Introductionmentioning

confidence: 99%

NSGA-II-Based Microchannel Structure Optimization Problem Study

Wang

¹

2022

Scientific Programming

1

0

1

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A multiobjective genetic algorithm is used to optimize the structure of circular concave cavities and microchannels. The objective functions of thermal resistance and pumping power are constructed by the response plane approximation method according to the simulation results, and then a mathematical model of multiobjective genetic optimization with the structural parameters of microchannels as variables is established. The Pareto optimized solution sets of thermal resistance and pumping power are calculated by the nondominated ranking genetic algorithm NSGA-II, and the comprehensive heat transfer performance is evaluated by the enhanced heat transfer factor. The results show that the multivariate statistical coefficients R 2 of the thermal resistance and pumping power objective functions are 0.932 9 and 0.996 6, respectively, indicating the high accuracy of the fitted functions. The optimized channel structure ( e 1 = 0.036.8 mm , e 2 = 0.019.3 mm ) was used to achieve a more uniform temperature field distribution and better integrated heat transfer performance (enhanced heat transfer factor η = 1.23 ). When the thermal resistance is larger or the pump work is larger, the comprehensive heat transfer effect is not as good as the working condition when the thermal resistance and pump work are more uniform.

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“…The NSGA-II algorithm can effectively solve multi-objective optimization problems. Compared with the NSGA, the NSGA-II has made improvements, and proposed a fast non-dominated sorting algorithm [21]. On the one hand, the computational complexity is reduced, and on the other hand, the parent population and the offspring population are merged, so that the next generation population is selected from a double space, thereby retaining all the best individuals.…”

Section: Solving Methodology 331 Response Surface Methodologymentioning

confidence: 99%

Multi-Objective Optimization of Forth Flotation Process: An Application in Gold Ore

Wen

¹

,

Yuan

²

,

Jia

³

et al. 2021

Sustainability

3

0

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In order to improve production control ability in the gold ore flotation process, the output index in this process was studied. Flotation is an effective gold recovery process. Gold concentrate grade and gold recovery rate are the key output indicators of the flotation process. However, in the existing studies exploring the impact of parameter changes on the output indicators, the control ability of the output indicators is insufficient, and the interaction between variables is inadequately considered. Therefore, a multi-objective optimization model based on response surface methodology and the non-dominated sorting genetic algorithm-II (NSGA-II) is proposed in this paper. Firstly, the experiment was designed based on the Box-Behnken principle. Based on the experimental results, the interaction between variables was analyzed and the response polynomial was fitted. Secondly, a multi-objective optimization model was constructed, and the NSGA-II was used to solve the model. Finally, an example of gold ore flotation was used to verify the effectiveness of the method. The optimal solution was a gold concentrate grade of 75.46 g/t and a gold recovery rate of 85.98%.

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“…The TOPSIS method has been studied to great length in recent years, and the best compromise solution has been determined. [45][46][47][48][49] The literature review presented earlier shows that researchers in various fields used TOPSIS method, but the principal component analysis (PCA) method with TOPSIS approach applied in B-pillar optimization design is not included in the literature. Therefore, in the present work, the PCA method with the TOPSIS is used in ranking the Pareto solutions, and some compromise optimum points compromising objective functions are found in this study.…”

Section: Introductionmentioning

confidence: 99%

A multi-objective optimization approach for simultaneously lightweighting and maximizing functional performance of vehicle body structure

Wang

¹

,

Wang

²

,

Xie

³

2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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This study presents a hybrid approach to integrate the comprehensive sensitivity analysis method, support vector machine technology, modified non-dominated sorting genetic algorithm-II method and the technique for order preference by similarity to ideal solution, which have been applied to multi-objective lightweight optimization of the B-pillar structure of an automobile. First, numerical models of the static–dynamic stiffness and the crashworthiness performance of automobile are established and validated by experimental testing. Then, the comprehensive sensitivity analysis method is used to define the final optimization variables. Experimental design and support vector machine based surrogate model techniques are introduced to establish the approximate model; subsequently, the modified non-dominated sorting genetic algorithm-II algorithm is applied to the multi-objective lightweight optimization design of the B-pillar structure, and the non-dominated solution set is determined. The principal component analysis method is applied to determine the weight of each objective. Finally, the technique for order preference by similarity to ideal solution method is used to rank Pareto front from best to worst to obtain the optimal solution; furthermore, a comparison between the original model and optimized design denotes that the mass of the B-pillar being reduced by 22.55% under the other impacting indicators is well guaranteed. Therefore, the proposed hybrid approach provided promising prospects in the lightweight and crashworthiness optimization application of the B-pillar.

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Modeling and combined application of the modified NSGA-II and TOPSIS to optimize a refrigerant-to-air multi-pass louvered fin-and-flat tube condenser

Cited by 23 publications

References 35 publications

NSGA-II-Based Microchannel Structure Optimization Problem Study

NSGA-II-Based Microchannel Structure Optimization Problem Study

Multi-Objective Optimization of Forth Flotation Process: An Application in Gold Ore

A multi-objective optimization approach for simultaneously lightweighting and maximizing functional performance of vehicle body structure

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