Design optimization of a shell-and-tube heat exchanger with disc-and-doughnut baffles for aero-engine using one hybrid method of NSGA II and MOPSO

Xu, Zhe; Ning, Xin; Yu, Zongling; Ma, Yanxing; Zhao, Zhihui; Zhao, B.

doi:10.1016/j.csite.2022.102644

Cited by 15 publications

(8 citation statements)

References 37 publications

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“…To quantify the stability of the disassembly sequence, we refer to the ideas of Kumar Gulivindala et al [37] and establish a connectivity matrix C m for the product to be dismantled. Equation (22) shows the connectivity matrix for a product with n components to be dismantled.…”

Section: Disassembly Stability (Ds)mentioning

confidence: 99%

“…Tey are widely applied in DLBP, such as ant colony algorithms [17], artifcial bee colony algorithms [18], variable neighborhood search algorithms [19], and artifcial fsh swarm algorithms [20]. In the feld of metaheuristic algorithms, NSGA-II is widely used in process optimization, workshop scheduling, and other areas due to its advantages of simple implementation and strong search capability and has achieved remarkable results [21][22][23]. Given the advantages of NSGA-II, some scholars have also used it to handle disassembly line balancing problems.…”

Section: Introductionmentioning

confidence: 99%

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A New Pareto Discrete NSGAII Algorithm for Disassembly Line Balance Problem

Xu,

Han,

et al. 2023

International Journal of Intelligent Systems

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With the increasing variety and quantity of end-of-life (EOL) products, the traditional disassembly process has become inefficient. In response to this phenomenon, this article proposes a random multiproduct U-shaped mixed-flow incomplete disassembly line balancing problem (MUPDLBP). MUPDLBP introduces a mixed disassembly method for multiple products and incomplete disassembly method into the traditional DLBP, while considering the characteristics of U-shaped disassembly lines and the uncertainty of the disassembly process. First, mixed-flow disassembly can improve the efficiency of disassembly lines, reducing factory construction and maintenance costs. Second, by utilizing the characteristics of incomplete disassembly to reduce the number of dismantled components and the flexibility and efficiency of U-shaped disassembly lines in allocating disassembly tasks, further improvement in disassembly efficiency can be achieved. In addition, this paper also addresses the characteristics of EOL products with heavy weight and high rigidity. While retaining the basic settings of MUPDLBP, the stability of the assembly during the disassembly process is considered, and a new problem called MUPDLBP_S, which takes into account the disassembly stability, is further proposed. The corresponding mathematical model is provided. To obtain high-quality disassembly plans, a new and improved algorithm called INSGAII is proposed. The INSGAII algorithm uses the initialization method based on Monte Carlo tree simulation (MCTI) and the Group Global Crowd Degree Comparison (GCDC) operator to replace the initialization method and crowding distance comparison operator in the NSGAII algorithm, effectively improving the coverage of the initial population individuals in the entire solution space and the evenness and spread of the Pareto front. Finally, INSGAII’s effectiveness has been affirmed by tackling both current disassembly line balancing problems and the proposed MUPDLBP and MUPDLBP_S. Importantly, INSGAII outshines six comparison algorithms with a top rank of 1 in the Friedman test, highlighting its superior performance.

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Section: Disassembly Stability (Ds)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Pareto Discrete NSGAII Algorithm for Disassembly Line Balance Problem

Xu,

Han,

et al. 2023

International Journal of Intelligent Systems

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“…NSGA-II algorithm [26], as a multiobjective optimization algorithm, can directly optimize and solve multi-objective problems with good optimization effect and fast optimization speed [27]. NSGA-II algorithm has been widely used in aerospace [28], machine design [29], reservoir optimization scheduling [30], resource scheduling [31], power systems [32], and many other fields. For example, in reservoir scheduling, Chang [33] et al applied the NSGA-II algorithm to the reservoir group optimal scheduling problem and tested the feasibility and effectiveness of the algorithm in the multi-objective optimal scheduling of reservoirs.…”

Section: Introductionmentioning

confidence: 99%

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

Xie,

Ma,

Wang

et al. 2024

Sustainability

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This paper establishes a multi-objective optimization model based on an improved NSGA-II algorithm, aiming to study the carbon reduction technology path of specific enterprises in the steel industry under the background of China’s dual-carbon goal and fill the research gap in the carbon reduction technology path of steel enterprises, which has certain guiding significance for the realization of China’s dual-carbon goal and the low-carbon development of steel enterprises. Firstly, through the analysis of the list of extreme energy efficiency technologies in the steel industry and the main process flow of steel industry production, the multi-objective optimization model is constructed from the two objective dimensions of maximum CO2 emission reduction and maximum enterprise economic benefit. Then the improved NSGA-II algorithm is used to solve the model. And the empirical analysis of a Hebei iron and steel enterprise, based on the technology application of enterprises before the release of the technology list, the technology path of enterprises to reduce carbon is predicted. The actual application data of the enterprise is used for verification and analysis, and suggestions on the technical path for the future low-carbon development of the enterprise are provided. The experimental results show that: (1) The optimal solution set of Pareto is consistent with the practical application of enterprises, and the constructed model is accurate and efficient, which can be used for the research of carbon reduction technology path. (2) When introducing technology, enterprises can give priority to the solution of common set technology based on their own needs.

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“…Sai and Rao 26 employed a hybrid optimization method, incorporating NSGA‐II, to optimize the design of a shell‐and‐tube heat exchanger, reporting that the hybrid method has a 4.85% and a 1.51% lower total cost in their two cases. By utilizing the Slipcevie method and experimental verification with one hybrid method of NSGA‐II and multiobjective particle swarm optimization, Xu et al 27 built a performance prediction model. Therefore, NSGA‐II is still an efficient alternative for practical heat exchanger applications.…”

Section: Introductionmentioning

confidence: 99%

Numerical thermal–hydraulic analysis and multiobjective design optimization of a printed circuit heat exchanger with airfoil overlap fin channels

Kuo

Xie

Chueh

2023

Engineering Reports

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In this study, we numerically investigated the performance of a printed circuit heat exchanger (PCHE) featuring National Advisory Committee for Aeronautics (NACA) 0020 airfoil overlap fins integrated into its straight flow channels. Numerical simulations were performed by solving Navier–Stokes and energy equations to analyze liquid water at temperatures ranging from 30 to 90°C, which is possible for use with a geothermal heating system, for example. The optimization of the PCHE airfoil fin geometry is performed using nondominated sorting genetic algorithm II (NSGA‐II) with three design features: front, back, and overlap lengths. The effectiveness and pressure drop of the PCHE are evaluated as two objective functions. The present study shows that, when a Reynolds number falls between 1088 and 5000, the overlapping airfoils exhibit lower pressure drops and higher convective heat flux relative to the separate airfoils, and an increase in overlap length always decreases the pressure drop positively. It is also found that using overlapping airfoils of front length of 0.1 mm, back length of 0.119 mm, and overlap length of 0.203 mm leads to almost the same effectiveness and a 22% decrease in pressure drop (which is generally believed to preferably maintain the high heat transfer performance and minimize pressure drop, as a favorable design), compared to a base design of the airfoils with front and back lengths of 0.2 mm and an overlap length of 0.1 mm.

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Design optimization of a shell-and-tube heat exchanger with disc-and-doughnut baffles for aero-engine using one hybrid method of NSGA II and MOPSO

Cited by 15 publications

References 37 publications

A New Pareto Discrete NSGAII Algorithm for Disassembly Line Balance Problem

A New Pareto Discrete NSGAII Algorithm for Disassembly Line Balance Problem

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

Numerical thermal–hydraulic analysis and multiobjective design optimization of a printed circuit heat exchanger with airfoil overlap fin channels

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