کنترل حلقه بسته بهینه جدایش جریان پله با بهره‌گیری از برنامه‌نویسی ژنتیکی

علوم کاربردی و محاسباتی در مکانیک

مقاله 1، دوره 37، شماره 3 - شماره پیاپی 41، شهریور 1404، صفحه 1-26   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.22067/jacsm.2024.88143.1261

نویسندگان

سیروس کسمائی^* ؛ مهران تاج‌فر‌؛ سامان کسمائی

دانشکده هوافضا، دانشگاه صنعتی امیرکبیر، تهران.

چکیده

در این پژوهش، روش نوین و بدون نیاز به مدل‌سازی و مبتنی بر یادگیری ماشین برای کنترل حلقه بسته جدایش پشت پله معرفی شده است. هدف اصلی این مطالعه، کاهش محدوده جریان بازگشتی پشت پله در عدد رینولدز 1350 است که توسط یک شکاف جت اینکار انجام می‌شود. در این مطالعه برپایه گسسته‌سازی حجم محدود، جریان به صورت پایا و دو بعدی شبیه‌سازی گردید. قوانین کنترل بازخوردی بر پایه یک تابع هزینه که شامل مساحت جریان بازگشتی و هزینه‌های مربوط به تزریق است، بهینه‌سازی شده‌اند. این فرآیند بهینه‌سازی با استفاده از الگوریتم‌های برنامه‌نویسی ژنتیکی صورت گرفته است. از برنامه‌نویسی ژنتیکی که مبتنی بر ساختار درخت است جهت ساخت انواع توابع مدل تزریق و ایجاد کنترل حلقه بسته سیستم استفاده شد. پس از گذشت 8 نسل با 500 نمونه در هر نسل، الگوریتم به یک قانون بازخوردی می‌رسد که قادر است محدوده جریان بازگشتی را تا 60% کاهش دهد. این سیستم کنترلی مبتنی بر یادگیری ماشین با بهترین تزریقگر حلقه باز که مبتنی بر پاشش با فرکانس کلوین-هلمهولتز است، مقایسه شد

کلیدواژه‌ها

کنترل جریان؛ برنامه‌نویسی ژنتیکی؛ شبیه‌سازی عددی؛ یادگیری ماشین؛ مکانیک سیالات محاسباتی

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