دانلود مقاله ISI انگلیسی شماره 145639
ترجمه فارسی عنوان مقاله

مقاله پژوهشی بررسی اپتیماسیون بر روی پارامترهای پیکربندی مبدل حرارتی مارپیچی زاویه با استفاده از سطح واکنش زنجیره ژنتیک و الگوریتم ژنتیک چند هدفه

عنوان انگلیسی
Research PaperOptimization investigation on configuration parameters of spiral-wound heat exchanger using Genetic Aggregation response surface and Multi-Objective Genetic Algorithm
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
145639 2017 24 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Thermal Engineering, Volume 119, 5 June 2017, Pages 603-609

ترجمه کلمات کلیدی
مبدل حرارتی اسپیرال زاویه، پارامترهای ساختاری ترکیب ژنتیکی، الگوریتم ژنتیک چند هدفه،
کلمات کلیدی انگلیسی
Spiral-wound heat exchanger; Structural parameters; Genetic Aggregation; Multi-Objective Genetic Algorithm;
پیش نمایش مقاله
پیش نمایش مقاله  مقاله پژوهشی بررسی اپتیماسیون بر روی پارامترهای پیکربندی مبدل حرارتی مارپیچی زاویه با استفاده از سطح واکنش زنجیره ژنتیک و الگوریتم ژنتیک چند هدفه

چکیده انگلیسی

Based on the method combining Genetic Aggregation response surface and Multi-Objective Genetic Algorithm, the effects of configuration parameters of spiral-wound heat exchanger (SWHE) on flow and heat transfer characteristics were numerically studied. The results show that the shell-side pressure drop of the spiral-wound heat exchanger decreases with the increase of layer pitch, winding angle and tube pitch, respectively. The shell-side heat transfer coefficient of the spiral-wound heat exchanger decreases with the increase of layer pitch and increases with the external diameter of tube. The shell-side heat transfer coefficient increases firstly with the increase of the winding angle and then decreases. The sensitivity analysis also shows that the shell-side flow and heat transfer characteristics are mainly affected by the winding angle. Under the working condition, the pressure drop and heat transfer coefficient are both negatively correlated with the layer pitch. And the winding angle is negatively correlated with the pressure drop, but positively correlated with the heat transfer coefficient. Three optimal configurations were obtained by the Multi-Object Genetic Algorithm based on Genetic Aggregation response surface. Compared with the original configuration, the average heat transfer coefficient of improved ones is enhanced by 2.93%, while the average pressure drop is reduced by 40.27%. The results are of great significance for the design of spiral-wound heat exchanger.