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Non-uniform magnetic field effects on the phase transition dynamics for PCM-installed 3D conic cavity having ventilation ports under hybrid nanofluid convection
被引:13
作者:
Selimefendigil, Fatih
[1
]
Oztop, Hakan F.
[2
,3
]
Izadi, Farhad
[4
]
机构:
[1] Celal Bayar Univ, Dept Mech Engn, TR-45140 Manisa, Turkey
[2] Firat Univ, Technol Fac, Dept Mech Engn, TR-23119 Elazig, Turkey
[3] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
[4] Islamic Azad Univ, Dept Mech Engn, Najafabad Branch, Najafabad, Iran
来源:
JOURNAL OF BUILDING ENGINEERING
|
2022年
/
49卷
关键词:
Hybrid nanofluid;
Non-uniform magnetic field;
Phase change;
3D vented cavity;
Finite element method;
HEAT-STORAGE-SYSTEM;
MHD NATURAL-CONVECTION;
NANO-ENHANCED-PCM;
MIXED CONVECTION;
SOLAR-ENERGY;
FORCED-CONVECTION;
SQUARE CAVITY;
PERFORMANCE;
INLET;
FLOW;
D O I:
10.1016/j.jobe.2022.104074
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
Effects of using non-uniform magnetic field in a PCM installed 3D vented cavity having triangular-cross section on the phase transition dynamics are numerically assessed. Alumina-copper nanoparticles are used in water as the heat transfer fluid. Numerical study is conducted for different Reynolds number (Re-between 100 and 500), Hartmann number (Ha-between 0 and 80), solid volume fraction of particles (svf-between 0.001 and 0.02), amplitude of non-uniform magnetic field (Amp-between 0.2 and 1) and aspect ratio of the cavity (AR-between 0.4 and 2). Phase transition becomes accelerated with higher Re, Ha, Amp, svf and AR. The reduction in phase transition time (tf) becomes 73% when lowest and highest Re cases are compared while by using nanoparticles at the highest amount, up to 42.9% reduction in complete transition time is obtained. For the highest amplitude of non-uniform magnetic field, 6.9% and 15% reduction amounts are obtained at Ha = 20 and Ha = 80. Faster transition times are observed with higher aspect ratio. Artificial neural networks are used for the dynamic characteristics estimations of phase change process while with 10 neuron in the hidden layer, successful estimations are ob-tained with network modeling approach.
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页数:17
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