بهینه‌سازی مبدل حرارتی فشرده به‌منظور کمینه‌سازی تولید آنتروپی با استفاده از الگوریتم تکامل تفاضلی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی شیمی دانشکده فنی دانشگاه گیلان

2 عضو هیات علمی گروه مهندسی شیمی دانشکده فنی دانشگاه گیلان

چکیده

با توجه به اهمیت مبدل­های حرارتی در واحدهای عملیاتی، در این پژوهش از الگوریتم تکامل تفاضلی (DE) برای بهینه­سازی مبدل حرارتی فشرده با هدف کمینه­سازی تعداد واحدهای تولید آنتروپی استفاده شده است. تعداد واحدهای تولید آنتروپی کل حرارتی و فشاری در مبدل حرارتی به‌عنوان تابع هدف و شش متغیر تصمیم‌گیری شامل طول مبدل، بسامد پره، طول پره، تعداد لایه­های عبور جریان در پرۀ آفست، ارتفاع پره و ضخامت پره با مجموعه­ای از قیدها، در نظر گرفته شده است .نتایج به‌دست‌آمده از بهینه­سازی با الگوریتم تکامل تفاضلی، با دو روش الگوریتم ژنتیک (GA) و تجمع ذرات (PSO)، مقایسه و اعتبارسنجی شد. میزان این الگوریتم در کمینه­سازی تولید آنتروپی (به میزان 5/1و 6/17درصد در مقایسه با روش تجمع ذرات و الگوریتم ژنتیک) نشان از توانایی بالای روش تکامل تفاضلی برای بهینه­سازی مبدل­های حرارتی فشرده دارد. همچنین، تأثیر تغییرات مؤلفه‌های کنترلی در الگوریتم تکامل تفاضلی بر هم‌گرایی و نیز میزان بهینه­سازی تابع هدف بررسی شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Optimization of Compact Heat Exchanger for Minimization of Entropy Generation Using Differential Evolution Algorithm

نویسندگان [English]

  • B. Maleki 1
  • S. Ashraf Talesh 2
1 University of Guilan
2 University of Guilan
چکیده [English]

Considering the importance of heat exchangers in operational units, in this research, the differential evolution (DE) algorithm was used to optimize compact heat exchanger aim to minimize the number of entropy generation units. The number of total entropy generation units of heat and pressure in the compact heat exchanger as an objective function and six decision variables including heat exchanger length, fin frequency, fin length, number of layers of flow on both sides of the offset strip fin, fin height, and fin thickness with a series of restrictions were Investigated. The results obtained from DE optimization were compared and validated by genetic algorithm (GA) and particle swarm optimization (PSO). The level of this algorithm in minimizing entropy generation (by 1.5 and 17.6% compared to the PSO method and GA) revealed high ability of the DE method in optimizing compact heat exchangers. Moreover, the effect of changes in control parameters in the DE algorithm on convergence and the degree of optimization of the objective function was studied.

کلیدواژه‌ها [English]

  • optimization
  • Differential evolution algorithm
  • Compact Exchanger
  • Entropy generation

 

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