بهبود ضرایب آیرودینامیکی ایرفویل با تغییرشکل آزاد به کمک شبکه‌های عصبی و الگوریتم ژنتیک

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی مکانیک ، دانشکده مهندسی ، دانشگاه فردوسی مشهد ، مشهد ، ایران

2 گروه مهندسی مکانیک، دانشکده مهندسی ، دانشگاه فردوسی مشهد، مشهد، ایران

چکیده

با ظهور ایرفویل‌های تغییرشکل‌پذیر، آیرودینامیک ایرفویل توربین‌های بادی و بال‌ها دچار تغییرات زیادی شد. در این پژوهش ضرایب آیرودینامیکی ایرفویل تغییر شکل‌پذیر بر مبنای ناکا۰۰۱۵ در محدوده عدد رینولدز 105 تا 106 و زاویه حمله‌ی 0 تا 12 درجه به کمک شبکه عصبی مصنوعی و الگوریتم ژنتیک بهینه‌سازی شده‌است. ابتدا ایرفویل‌ها به وسیله نقاط کنترل تصادفی در نرم افزار متلب تولید و در نرم افزار گمبیت شبکه‌بندی شدند، سپس در نرم افزار انسیس به صورت دو‌بعدی شبیه‌سازی شدند. نتایج حاصل از شبیه‌سازی شامل ضرایب برآ و پسآ، نقطه‌ی جدایش و مرکز فشار به همراه نقاط کنترل ایرفویل برای آموزش شبکه عصبی مورد استفاده قرارگرفتند. تابع آموزش دیده شبکه عصبی به عنوان تابع ورودی به الگوریتم ژنتیک داده می‌شود تا ضرایب مورد نظر بهینه‌سازی شوند.  ضریب برآ، مرکز فشار، نقطه‌ی جدایش و نسبت ضریب برآ به پسآ به صورت تک هدفه بهینه‌سازی شدند، در بهینه‌سازی تک هدفه ضریب برآ با استفاده از ایرفویل تغییرشکل‌پذیر مقدار ضریب برآ 18% افزایش یافت. همچنین ضریب برآ و مرکز فشار، ضریب برآ و پسآ به صورت دو هدفه بهینه‌سازی شدند. در بهینه‌سازی دو هدفه ضریب برآ و پسآ، با تغییر شکل ایرفویل مقادیر آن‌ها به ترتیب در 0/8 و 0/03 کنترل شد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Improving the power coefficient of the Darrieus vertical axis wind turbine with the aid of morphing airfoils

نویسندگان [English]

  • Mohsen Kazemi 1
  • Amirhossein Fardi 1
  • Mohammad Javad Maghrebi 2
1 Department of mechanical engineering , faculty of engineering , Ferdowsi University of Mashhad , Mashhad , Iran
2 Department of mechanical engineering , faculty of engineering , Ferdowsi University of Mashhad, Mashhad, Iran
چکیده [English]

With the advent of smart materials in recent years, the aviation industry and airfoils have undergone many changes.Research into the use of smart materials in aircraft wings to increase their performance and then the use of smart materials in wind turbine airfoils has begun. In this study, computational fluid dynamics and unsteady Reynolds averaged Navier Stokes equations for a three-bladed Darrieus wind turbine equipped with a morphing airfoil were used to determine the optimum blade cross-section.250 airfoils were generated by random control points, in Gambit software, they were unstructured and generated as a sliding mesh then they were simulated in 2D Ansys by using pressure-implicit with the splitting of operators algorithm.Control points and power coefficient were used for artificial neural network trainingand the genetic algorithm was used to optimize the power coefficient. In this study, the base airfoil is NACA0015. The results of that have been very effective. For the first case (Determine the optimal cross-section of the turbine at a full round) the power coefficient of Darrieus wind turbine with the optimal cross-section increased by 42%, and the blade section(airfoil) was also drawn. For the second case (Determine the optimal cross-section in each of the four zones of the rotor), the most efficient sections (airfoils) in four-zone were obtained, increasing the turbine power coefficient by 60% was the result of this optimization.

کلیدواژه‌ها [English]

  • power coefficient
  • Computational fluid dynamic
  • Darrieus wind turbine
  • artificial neural network
  • genetic algorithm
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