کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
4990827 1368115 2018 8 صفحه PDF ندارد دانلود رایگان
عنوان انگلیسی مقاله
Research PaperPrice-performance evaluation of thermal conductivity enhancement of nanofluids with different particle sizes
ترجمه فارسی عنوان
ارزیابی هزینه ـ عملکرد ارتقاء هدایت حرارتی نانوسیم ها با اندازه های مختلف ذرات
کلمات کلیدی
انتقال حرارت؛ نانوفیلد؛ رسانایی گرمایی؛ تجزیه و تحلیل قیمت ـ عملکرد؛ شبکه های عصبی مصنوعی؛ مدل سازی؛
Heat transfer; Nanofluid; Thermal conductivity; Price-performance analysis; Artificial neural network; Modeling;
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی جریان سیال و فرایندهای انتقال
چکیده انگلیسی

•Comparison between thermal conductivity of MgO and Fe/EG based nanofluid.•Introduction of a new index for measuring the efficiency of nanofluids.•Comparison between 2 nanofluids in terms of PPF.•Proposing a new model to calculate the thermal conductivity of nanofluids.•Modeling data of nanofluids using artificial neural network.

The nanofluid's thermal conductivity has been one of the most fascinating topics for researchers in this field. So far, a large number of aqueous, non-aqueous and also oleic nanofluids are experimentally studied. These nanofluids have been investigated with different volume fractions, various particle sizes and different production methods. But, the question seems to be very important now is that among available nanofluids, which one can meet our needs better? What particle sizes will work best for a chosen nanoparticle? Whether pure experimental measuring is reliable for using a nanofluid in the industry or not? Two nanofluids of Fe and MgO in Ethylene Glycol base-fluid with various particle sizes have been probed in this research, and the preparation cost of these nanofluids is compared with their thermal performance and proportionate responses are given to above questions. As well, a correlation is provided in order to measure thermal conductivity of nanofluids in terms of thermal conductivity, particle size, temperature and volume fraction of nanoparticles, and the data were compared with the result obtained from a neural network modeling.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Thermal Engineering - Volume 128, 5 January 2018, Pages 373-380
نویسندگان
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