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]

Improvement of aerodynamic coefficients of the airfoil with free form deformation with the aid of Artificial Neural Networks and Genetic Algorithm

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 morphing airfoils, the aerodynamics of wind turbines and wings underwent many changes. In this study, the aerodynamic coefficients of morphing airfoil based on NACA 0015 are optimized in the range of Reynolds number 105 to 106 and the angle of attack 0 to 12 degrees using Artificial Neural Network (ANN) and Genetic Algorithm (GA). First, the airfoils were created in MATLAB software by random control points and mesh generated in Gambit software, then in two-dimensional Ansys software were simulated. The simulation results, including lift and drag coefficients, separation point and pressure center, with control points were used to train the Artificial Neural Network (ANN). The trained function is given as an input function to the Genetic Algorithm (GA) to optimize the desired coefficients.
Lift coefficient, center of pressure, separation point and lift to drag ratio were optimized as a single objective, In single-objective optimization, the lift coefficient was increased by 18% using the morphing airfoil. Also, the lift coefficient and the center of pressure, the lift coefficient and the drag coefficient were optimized as the dual-objectives optimization. In the optimization of the dual objectives, lift and drag coefficients were controlled by 0.8 and 0.03, respectively, by the morphing airfoils.

کلیدواژه‌ها [English]

  • Power coefficient
  • Computational fluid dynamic
  • Darrieus wind turbine
  • Artificial neural network
  • Genetic algorithm

مراجع

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نشریه مهندسی مکانیک امیرکبیر
دوره 53، شماره 7
مهر 1400
صفحه 4113-4132

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