کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7374653 | 1480063 | 2018 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using artificial neural network for investigating of concurrent effects of multi-walled carbon nanotubes and alumina nanoparticles on the viscosity of 10W-40 engine oil
ترجمه فارسی عنوان
با استفاده از شبکه عصبی مصنوعی برای بررسی اثرات همزمان نانولوله های کربنی چند ضلعی و نانوذرات آلومینای بر ویسکوزیته روغن موتور 10 وات
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
فیزیک ریاضی
چکیده انگلیسی
The present study used artificial neural networks (ANNs) and experimental data to model the viscosity of the MWCNT (50%)-Al2O3 (50%)/10W40 hybrid nanofluid at different temperatures from 5 to 55 °C and for nanoparticle volume fractions of 0.05% to 1%. An ANN and a new correlation as function of solid volume fraction, temperature and shear rate. The multidimensional MLP-ANN was employed and investigated as the learning algorithm. The R-squared values for the proposed correlation and ANN were obtained to be 0.9973 and 0.9944, respectively. In order to analyze the importance of each term of correlation, p-value of parameters is determined. Also one factor and two factor analysis of viscosity are presented in this study. According to one and two factor analysis results, temperature changes has the highest effect on viscosity. Shear rate and solid volume fraction effects on viscosity are in next level of importance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 510, 15 November 2018, Pages 610-624
Journal: Physica A: Statistical Mechanics and its Applications - Volume 510, 15 November 2018, Pages 610-624
نویسندگان
Mohammad Hemmat Esfe, Mohammad Hassan Kamyab, Masoud Afrand, Mahmoud Kiannejad Amiri,