کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1553882 998760 2012 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Experimental and numerical investigation of heat transfer in a miniature heat sink utilizing silica nanofluid
موضوعات مرتبط
مهندسی و علوم پایه مهندسی مواد مواد الکترونیکی، نوری و مغناطیسی
پیش نمایش صفحه اول مقاله
Experimental and numerical investigation of heat transfer in a miniature heat sink utilizing silica nanofluid
چکیده انگلیسی

In this paper, heat transfer characteristics of a miniature heat sink cooled by SiO2–water nanofluids were investigated both experimentally and numerically. The heat sink was fabricated from aluminum and insulated by plexiglass cover plates. The heat sink consisted of an array of 4 mm diameter circular channels with a length of 40 mm. Tests were performed while inserting a 180 W/cm2 heat flux to the bottom of heat sink and Reynolds numbers ranged from 400 to 2000. The three-dimensional heat transfer characteristics of the heat sink were analyzed numerically by solving conjugate heat transfer problem of thermally and hydrodynamically developing fluid flow. Experimental results showed that dispersing SiO2 nanoparticles in water significantly increased the overall heat transfer coefficient while thermal resistance of heat sink was decreased up to 10%. Numerical results revealed that channel diameter, as well as heat sink height and number of channels in a heat sink have significant effects on the maximum temperature of heat sink. Finally, an artificial neural network (ANN) was used to simulate the heat sink performance based on these parameters. It was found that the results of ANN are in excellent agreement with the mathematical simulation and cover a wider range for evaluation of heat sink performance.


► SiO2–water nanofluid as coolant in a miniature heat sink.
► SiO2–water nanofluid significantly increases the overall heat transfer coefficient compared to water.
► Thermal resistance of heat sink decreases up to 10%.
► Channel diameter, heat sink height and number of channels have significant effects on the maximum temperature of heat sink.
► Artificial neural network (ANN) covers a wider range for evaluation of heat sink performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Superlattices and Microstructures - Volume 51, Issue 2, February 2012, Pages 247–264
نویسندگان
, , , ,