کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
653012 1457486 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی جریان سیال و فرایندهای انتقال
پیش نمایش صفحه اول مقاله
Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid
چکیده انگلیسی

This paper focuses on designing an artificial neural network which can predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluids from input experimental data including temperature, diameter of particles, and solid volume fraction. The experimental data were extracted and they were used as learning dataset to train the neural network. To find a proper architecture for network, an iteration method was used. Based on the results, there was no over-fitting in designed neural network and the neural network was able to track the data. ANN outputs showed that the maximum errors in predicting thermal conductivity and dynamic viscosity are 2% and 2.5%, respectively. Based on the ANN outputs, two sets of correlations for estimating the thermal conductivity and dynamic viscosity were presented. The comparisons between experimental data and the proposed correlations showed that the presented correlations were in an excellent agreement with experimental data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Communications in Heat and Mass Transfer - Volume 68, November 2015, Pages 50–57
نویسندگان
, , , , ,