مقایسۀ عملکرد هیدرودینامیکی سه نوع همزن استاتیکی با استفاده از دینامیک سیالات محاسباتی و شبکۀ عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

کردستان، سنندج، دانشگاه کردستان، دانشکده مهندسی، گروه مهندسی شیمی

چکیده

همزن‌های استاتیک تجهیزاتی برای آمیزش در راکتورهای شیمیایی و افزایش ضریب انتقال حرارت در مبدل‌های حرارتی هستند. در این تحقیق مشخصه‌های جریان سیال در لوله‌های مجهز به همزن‌های استاتیکی اصلاح‌شده با ابعاد هندسی متفاوت با روش شبیه‌سازی دینامیک سیالات محاسباتی بررسی شده است. همزن‌های نوارپیچیدۀ کلاسیک، نوارپیچیدۀ حفره‌دار و نوارپیچیدۀ V-Cut برای اعداد رینولدز 3000 تا 19000 بررسی شدند. الگوی جریان و افت فشار برای جریان سیال بر روی این همزن‌ها بررسی شد. هم‌چنین پس از تأیید اعتبار نتایج شبیه‌سازی، داده‌های به‌دست‌آمده برای آموزش مدل شبکۀ عصبی مصنوعی استفاده شد. عدد رینولدز و مؤلفه‌های هندسی همزن‌ها به‌عنوان متغیرهای ورودی شبکۀ عصبی برای تخمین ضریب اصطکاک استفاده‌ شدند. کارایی مدل‌ها در تخمین ضریب اصطکاک ارزیابی شد که نتایج بیانگر خطای نسبی کمتر از 1 درصد است. خطای نسبی برای کلیۀ داده‌ها در حالت کلاسیک، V-Cut و حفره‌دار به‌ترتیب 75/0%، 57/0% و 52/0% و برای داده‌های ارزیابی به‌ترتیب 1/1%، 92/0% و 62/0% به دست آمد. 30 درصد داده‌ها به‌طور تصادفی برای ارزیابی شبکۀ عصبی در نظر گرفته شد که دقت بالای تخمین آن‌ها اعتبار مدل را اثبات می‌کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparison of Hydrodynamic Performance of Three Types of Static Mixers Using Computational Fluid Dynamics and Artificial Neural Network

چکیده [English]

Static mixers are applied for increasing the mixing in chemical reactors as well as for increasing the heat transfer coefficient in heat exchangers. In the study, fluid flow characteristics in tubes equipped with modified static mixers with different geometric parameters were investigated by computational fluid dynamics. The classic twisted tape, perforated twisted tape, and V-Cut twisted tape were evaluated for Reynolds numbers between of 3000 to 19000. The fluid flow and pressure drop for the mixers were investigated. The validated simulation results were employed to train the artificial neural network model. Reynolds number and geometric parameters of the mixers were used as input variables of the neural network for predicting the friction factor. The model accuracy for estimating the friction factor was investigated and a relative error of less than 1% was obtained. The main relative errors for all data in classical, V-Cut, and perforated twisted tape were 0.75%, 0.57%, and 0.52%, respectively, and for validation data were 1.1%, 0.92%, and 0.62%. 30% of the data were randomly selected for the neural network to prove the model validity.

کلیدواژه‌ها [English]

  • Static Mixers
  • friction factor
  • Twisted Tape
  • Computational Fluid Dynamics
  • Artificial Neural Network
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