دانلود مقاله ISI انگلیسی شماره 98226
ترجمه فارسی عنوان مقاله

تجزیه و تحلیل عددی و بررسی بهینه سازی عملکرد اجزای پوسته یک مبدل حرارتی پوسته و لوله با بافرهای متفرقه

عنوان انگلیسی
Numerical analysis and optimization study on shell-side performances of a shell and tube heat exchanger with staggered baffles
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
98226 2018 13 صفحه PDF
منبع

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

Journal : International Journal of Heat and Mass Transfer, Volume 124, September 2018, Pages 247-259

ترجمه کلمات کلیدی
مبدل حرارتی شل و لوله، شبیه سازی عددی، افزایش انتقال حرارت، شبکه های عصبی مصنوعی، بهینه سازی چند هدفه،
کلمات کلیدی انگلیسی
Shell and tube heat exchanger; Numerical simulation; Heat transfer enhancement; Artificial neural network; Multi-objective optimization;
پیش نمایش مقاله
پیش نمایش مقاله  تجزیه و تحلیل عددی و بررسی بهینه سازی عملکرد اجزای پوسته یک مبدل حرارتی پوسته و لوله با بافرهای متفرقه

چکیده انگلیسی

With a view to possessing the characteristics of the simple fabrication of the shell and tube heat exchanger with segmental baffles (STHX-SG) and the helical flow of the shell and tube heat exchanger with continuous helical baffles (STHX-CH), a shell and tube heat exchanger with staggered baffles (STHX-ST) is proposed in this work. The baffles of the STHX-ST are arranged according to a certain rule that the adjacent baffles are staggered by a constant clockwise or counterclockwise angle in sequence. Comparisons of the heat transfer performance and pressure drop among the STHX-SG, STHX-CH, and STHX-ST are firstly carried out. Results show that the comprehensive performance of the STHX-ST is superior the STHX-SG and STHX-CH. The parametric studies about the baffle cut δ and staggered angle β are conducted for the STHX-ST. Moreover, the multi-objective optimization is carried out to obtain the optimal solutions using the genetic algorithm further. The relationships between the design variables (the baffle cut δ, staggered angle β, and number of baffles n) and objective functions (the heat transfer rate Q and pressure drop Δp) are characterized by the artificial neural networks. The STHX-ST, at the δ = 0.45, β = 79°, and n = 11, is determined as the optimal solution according to the TOPSIS selection. Meanwhile, it is proved that the STHX-SG, a special STHX-ST at the β = 180°, is not always the best choice from the view of heat transfer enhancement. The STHX-ST can provide a preferable and meaningful solution for more efficient energy utilization in industrial applications.