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Computational and Experimental Evaluation of Nanofluids in Heating and Cooling Forced Convection Applications.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Computational and Experimental Evaluation of Nanofluids in Heating and Cooling Forced Convection Applications./
作者:	Strandberg, Roy.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	175 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:	Dissertations Abstracts International82-11B.
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28414524
ISBN:	9798728256885

Computational and Experimental Evaluation of Nanofluids in Heating and Cooling Forced Convection Applications.
Strandberg, Roy.

Computational and Experimental Evaluation of Nanofluids in Heating and Cooling Forced Convection Applications. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 175 p.

Source: Dissertations Abstracts International, Volume: 82-11, Section: B.

Thesis (Ph.D.)--University of Alaska Fairbanks, 2021.

This item must not be sold to any third party vendors.

The purpose of the research was to examine the heat transfer and fluid dynamic performance of various nanofluids in heating and cooling applications using empirical and computational methods. Two experiments were performed to characterize and compare the performance of a Al2O3/60% ethylene glycol (60% EG) nanofluid to that of its base fluid. In the first experiment, the nanofluid was comprised of Al2O3 nanoparticles with 1% volumetric concentration in a 60% ethylene glycol/40% water (60% EG by mass) solution to that of 60%EG in a liquid to air heat exchanger. The test bed used in the experiment was built to simulate a small air handling system typical of that used in heating, ventilating and air conditioning (HVAC) applications. Previously established empirical correlations for thermophysical properties of fluids were used to determine the values of various parameters (e.g. Nusselt number, Reynolds number, and Prandtl number). The testing shows that the 1% Al2O3 nanofluid generates a marginally higher heat rate than the 60% EG under certain conditions. At Re=3,000, the nanofluid produced a heat rate that was 2% higher than that of the 60% EG. The empirically determined Nusselt number associated with the convection inside the coil tubing follows the behavior predicted by the Dittus-Boelter correlation quite well (R2=0.97), while the empirically determined Nusselt number for the 60% EG follows the Petukhov correlation similarly well (R2=0.97). Pressure loss and hydraulic power for the nanofluid were higher than for the base fluid over the range of conditions tested. The exergy destroyed in the heat exchange and fluid flow processes were between 8 and 13% higher for the nanofluid over the tested range of Reynolds numbers.The objective of the second study was to experimentally characterize and compare the performance of a nanofluid comprised of Al2O3 nanoparticles with 1, 2 and 3% volumetric concentrations in a 60% EG solution to that of 60% EG in a liquid to air heat exchanger. In this experiment, the heating system was operated in a higher temperature regime than in the first experiment. As in the first experiment, the test bed used in the experiment simulated a small air handling system typical of that used in HVAC applications. Entering conditions for the air and liquid were selected to emulate typical operating conditions of commercial air handling systems in sub arctic regions (such as Alaska). In the experiment the nanofluids generally did not perform as well as expected based on previous analytical work. The performance of the 1% nanofluid was generally equal to that of the base fluid considering identical entering conditions. However, the 2% and 3% nanofluids performance was considerably worse than that of the base fluid. The higher concentration nanofluids exhibited heat rates up to 14.6% lower than that of the 60%EG, and up to 44.3% lower heat transfer coefficient. The 1% Al2O3/60% EG exhibited 100% higher pressure drop across the coil than the base fluid considering equal heat output. In the computational portion of the research, the performance of a microchannel heat sink (MCHS), similar to those used to cool microprocessors filled with various nanofluids and the corresponding base fluid without nanoparticles are examined. The MCHS is modeled using a three-dimensional conjugate heat transfer and fluid dynamic finite-volume model over a range of conditions. The model incorporates a fixed heat flux of 1,000,000 W/m2 at the base of the solid domain. The thermophysical properties of the fluids are based on empirically obtained correlations, and vary with temperature. Nanofluids considered include 60% Ethylene Glycol/40% Water solutions with CuO, SiO2, and Al2O3 nanoparticles dispersed in volumetric concentrations ranging from 1 to 3%. The flow conditions analyzed are in the laminar range (50≤Re≤300), and consider multiple inlet temperatures. The analyses predict that when compared on an equal Reynolds number basis, the 60%EG/3% CuO nanofluid exhibits the highest heat transfer coefficient, and the largest reduction in average base temperature. At an inlet Reynolds number of 300, and an inlet temperature of 308K the nanofluid is predicted to have an average heat transfer coefficient that is 30% higher than that of the base fluid, while the average temperature on the base of the heat exchanger is 1K lower than that of the base fluid. In contrast, the inlet pressure required for these entering conditions is 192% higher than that for the base fluid, while the required hydraulic power to drive the flow is 366% higher than that of the base fluid. The enhanced heat transfer performance potential of nanofluids comes at the expense of generally higher pumping power consumption.

ISBN: 9798728256885Subjects--Topical Terms:

649730
Mechanical engineering.
Subjects--Index Terms:

Nanofluids

Computational and Experimental Evaluation of Nanofluids in Heating and Cooling Forced Convection Applications.
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506 $a This item must not be sold to any third party vendors.
520 $a The purpose of the research was to examine the heat transfer and fluid dynamic performance of various nanofluids in heating and cooling applications using empirical and computational methods. Two experiments were performed to characterize and compare the performance of a Al2O3/60% ethylene glycol (60% EG) nanofluid to that of its base fluid. In the first experiment, the nanofluid was comprised of Al2O3 nanoparticles with 1% volumetric concentration in a 60% ethylene glycol/40% water (60% EG by mass) solution to that of 60%EG in a liquid to air heat exchanger. The test bed used in the experiment was built to simulate a small air handling system typical of that used in heating, ventilating and air conditioning (HVAC) applications. Previously established empirical correlations for thermophysical properties of fluids were used to determine the values of various parameters (e.g. Nusselt number, Reynolds number, and Prandtl number). The testing shows that the 1% Al2O3 nanofluid generates a marginally higher heat rate than the 60% EG under certain conditions. At Re=3,000, the nanofluid produced a heat rate that was 2% higher than that of the 60% EG. The empirically determined Nusselt number associated with the convection inside the coil tubing follows the behavior predicted by the Dittus-Boelter correlation quite well (R2=0.97), while the empirically determined Nusselt number for the 60% EG follows the Petukhov correlation similarly well (R2=0.97). Pressure loss and hydraulic power for the nanofluid were higher than for the base fluid over the range of conditions tested. The exergy destroyed in the heat exchange and fluid flow processes were between 8 and 13% higher for the nanofluid over the tested range of Reynolds numbers.The objective of the second study was to experimentally characterize and compare the performance of a nanofluid comprised of Al2O3 nanoparticles with 1, 2 and 3% volumetric concentrations in a 60% EG solution to that of 60% EG in a liquid to air heat exchanger. In this experiment, the heating system was operated in a higher temperature regime than in the first experiment. As in the first experiment, the test bed used in the experiment simulated a small air handling system typical of that used in HVAC applications. Entering conditions for the air and liquid were selected to emulate typical operating conditions of commercial air handling systems in sub arctic regions (such as Alaska). In the experiment the nanofluids generally did not perform as well as expected based on previous analytical work. The performance of the 1% nanofluid was generally equal to that of the base fluid considering identical entering conditions. However, the 2% and 3% nanofluids performance was considerably worse than that of the base fluid. The higher concentration nanofluids exhibited heat rates up to 14.6% lower than that of the 60%EG, and up to 44.3% lower heat transfer coefficient. The 1% Al2O3/60% EG exhibited 100% higher pressure drop across the coil than the base fluid considering equal heat output. In the computational portion of the research, the performance of a microchannel heat sink (MCHS), similar to those used to cool microprocessors filled with various nanofluids and the corresponding base fluid without nanoparticles are examined. The MCHS is modeled using a three-dimensional conjugate heat transfer and fluid dynamic finite-volume model over a range of conditions. The model incorporates a fixed heat flux of 1,000,000 W/m2 at the base of the solid domain. The thermophysical properties of the fluids are based on empirically obtained correlations, and vary with temperature. Nanofluids considered include 60% Ethylene Glycol/40% Water solutions with CuO, SiO2, and Al2O3 nanoparticles dispersed in volumetric concentrations ranging from 1 to 3%. The flow conditions analyzed are in the laminar range (50≤Re≤300), and consider multiple inlet temperatures. The analyses predict that when compared on an equal Reynolds number basis, the 60%EG/3% CuO nanofluid exhibits the highest heat transfer coefficient, and the largest reduction in average base temperature. At an inlet Reynolds number of 300, and an inlet temperature of 308K the nanofluid is predicted to have an average heat transfer coefficient that is 30% higher than that of the base fluid, while the average temperature on the base of the heat exchanger is 1K lower than that of the base fluid. In contrast, the inlet pressure required for these entering conditions is 192% higher than that for the base fluid, while the required hydraulic power to drive the flow is 366% higher than that of the base fluid. The enhanced heat transfer performance potential of nanofluids comes at the expense of generally higher pumping power consumption.
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653 $a Nanofluids
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