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Multi-objective shape optimization of a plate-fin heat exchanger using CFD and multi-objective genetic algorithm

机译:基于CFD和多目标遗传算法的板翅式换热器多目标形状优化

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摘要

A theoretical optimization was carried out to develop a plate-fin heat exchanger for the hydraulic retar-der. CFD simulation and multi-objective optimization were combined to improve the performances of the original heat exchanger, which could not be applied to the practical engineering application. The optimizations of the Colburn factor j and the friction factor f were treated as the multi-objective optimization problem due to the presence of two conflicting objectives. The second generation Non-Dominated Sorting Genetic Algorithm (NSGA-II) was employed to optimize the shape of the heat exchanger. The optimization results indicated that the Colburn factor j increased by 12.83% and the friction factor f decreased by 26.91%, which showed that the convective heat transfer was enhanced and the flow resistance was also significantly reduced. Then, internal flow fields involving temperature, pressure and velocity were qualitatively compared to further emphasize the optimization effect. Finally, the field synergy numbers were compared and analyzed, which could help to prove the rationality of the optimized result and guide the following design or optimization tasks.
机译:进行了理论上的优化,以开发用于水力缓凝器的板翅式热交换器。 CFD仿真与多目标优化相结合,提高了原有换热器的性能,无法应用于实际工程中。由于存在两个相互冲突的目标,因此将Colburn因子j和摩擦因子f的优化视为多目标优化问题。第二代非支配排序遗传算法(NSGA-II)用于优化热交换器的形状。优化结果表明,Colburn因子j增加了12.83%,摩擦因子f减少了26.91%,这表明对流换热得到增强,流阻也显着降低。然后,定性地比较了涉及温度,压力和速度的内部流场,以进一步强调优化效果。最后,对现场协同数进行了比较和分析,有助于证明优化结果的合理性,并指导后续的设计或优化任务。

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