کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5450323 1512862 2017 24 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting the effects of magnesium oxide nanoparticles and temperature on the thermal conductivity of water using artificial neural network and experimental data
ترجمه فارسی عنوان
پیش بینی اثر نانوذرات اکسید منیزیم و درجه حرارت بر هدایت حرارتی آب با استفاده از شبکه عصبی مصنوعی و داده های تجربی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد مواد الکترونیکی، نوری و مغناطیسی
چکیده انگلیسی
The current paper first presents an empirical correlation based on experimental results for estimating thermal conductivity enhancement of MgO-water nanofluid using curve fitting method. Then, artificial neural networks (ANNs) with various numbers of neurons have been assessed by considering temperature and MgO volume fraction as the inputs variables and thermal conductivity enhancement as the output variable to select the most appropriate and optimized network. Results indicated that the network with 7 neurons had minimum error. Eventually, the output of artificial neural network was compared with the results of the proposed empirical correlation and those of the experiments. Comparisons revealed that ANN modeling was more accurate than curve-fitting method in the predicting the thermal conductivity enhancement of the nanofluid.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica E: Low-dimensional Systems and Nanostructures - Volume 87, March 2017, Pages 242-247
نویسندگان
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