کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
644783 1457134 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Heat exchanger network retrofit throughout overall heat transfer coefficient by using genetic algorithm
ترجمه فارسی عنوان
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موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی جریان سیال و فرایندهای انتقال
چکیده انگلیسی


• An optimization model using GA is developed to retrofit the existing HEN.
• The retrofitting increased the amount of energy recovery by optimizing the value of overall heat transfer coefficient (U).
• Three types of optimization scenarios are conducted with different constraint of U.

Heat integration through energy recovery is utilized to reduce energy consumption. Energy or heat recovery can be performed using heat exchanger (HE) in heat exchanger network (HEN). HEN is an arrangement of several interconnected HE, which is used to conduct heat recovery. This arrangement increases complexity of heat integration. In the existing HEN, some of the energy is wasted due to unproper HEN design. HEN retrofit can overcome this problem and increase the heat recovery in existing processes. In this research, HEN retrofit is performed by optimizing the maximum heat recovery (Q) without changing the area of heat transfer or adding new HE and the arrangement of HE in HEN. In order to fid out the maximum Q, genetic algorithm (GA) is used to search the best heat transfer coefficient (U) value. In this paper, three cases of optimization scenarios are performed by some constraints considered on the HEN model. In the first optimization scenario, U is optimized without the given the maximum and minimum limits. While in the second optimization scenario, U has limitation at the minimum value, which is the value of U on the initial design data. And on the third case optimization scenario, U has limits due to availability of existing technology, which is the increase in the maximum of U using internal fins, twisted tape insert, coiled wire insert, and helical baffle. Heat recovery obtained in the first case scenario optimization results was at 13.21%, whereas the second case scenario optimization was at 9.14%, and the third case scenario optimization was at 3.60% with an internal fin technology limitations, 2.77% by limitations of twisted tape inserts technology, 7.69% with coiled wire insert technology, and 4.61% with helical baffles technology.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Thermal Engineering - Volume 94, 5 February 2016, Pages 274–281
نویسندگان
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