کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7054829 1458022 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Artificial neural network analysis the pulsating Nusselt number and friction factor of TiO2/water nanofluids in the spirally coiled tube with magnetic field
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی جریان سیال و فرایندهای انتقال
پیش نمایش صفحه اول مقاله
Artificial neural network analysis the pulsating Nusselt number and friction factor of TiO2/water nanofluids in the spirally coiled tube with magnetic field
چکیده انگلیسی
The application of artificial neural network to analyze the pulsating nanofluids heat transfer and pressure drop in the spirally coiled tube with magnetic field are presented. Four different training algorithms of Levenberg-Marquardt Backwardpropagation (LMB), Scaled Conjugate Gradient Backpropagation (SCGB), Bayesian Regulation Backpropagation (BRB), and Resilient Backpropagation (RB) are applied to adjust errors for obtaining the optimal ANN model. The results obtained from the artificial neural network are compared those from the present experiment. It is found that the Levenberg- Marquardt Backpropagation algorithm gives the minimum MSE, and maximum R as compared with other training algorithms. Based on the optimal ANN model, the majority of the data falls within ±2.5%, ±5% of the Nusselt number and friction factor, respectively. The obtained optimal ANN has been applied to predict the thermal performance of the spirally coiled tube with magnetic field.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Heat and Mass Transfer - Volume 118, March 2018, Pages 1152-1159
نویسندگان
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