کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
653449 | 1457511 | 2013 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Viscosity of nanofluids based on an artificial intelligence model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
جریان سیال و فرایندهای انتقال
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
By using an FCM-based Adaptive neuro-fuzzy inference system (FCM-ANFIS) and a set of experimental data, models were developed to predict the effective viscosity of nanofluids. The effective viscosity was selected as the target parameter, and the volume concentration, temperature and size of the nanoparticles were considered as the input (design) parameters. To model the viscosity, experimental data from literature were divided into two sets: a train and a test data set. The model was instructed by the train set and the results were compared with the experimental data set. The predicted viscosities were compared with experimental data for four nanofluids, which were Al2O3, CuO, TiO2 and SiO2, and with water as base fluid. The viscosities were also compared with several of the most cited correlations in literature. The results, which were obtained by the proposed FCM-ANFIS model, in general compared very well with the experimental measurement.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Communications in Heat and Mass Transfer - Volume 43, April 2013, Pages 16-21
Journal: International Communications in Heat and Mass Transfer - Volume 43, April 2013, Pages 16-21
نویسندگان
M. Mehrabi, M. Sharifpur, J.P. Meyer,