ZHOU Jianyang, LUO Xiaoping, XIE Mingyu, et al. Influence of nanoparticle concentration on pressure drop of Al2O3/R141b boiling flow in micro heat exchanger by direct metal laser sintering[J]. CIESC Journal, 2016, (11): 4587-4598. DOI: 10.11949/j.issn.0438-1157.20160634.
ZHOU Jianyang, LUO Xiaoping, XIE Mingyu, et al. Influence of nanoparticle concentration on pressure drop of Al2O3/R141b boiling flow in micro heat exchanger by direct metal laser sintering[J]. CIESC Journal, 2016, (11): 4587-4598. DOI: 10.11949/j.issn.0438-1157.20160634.DOI:
Uniform and stable nanorefrigerant coolants of 0.05%-0.4% Al2O3/R141b (mass fraction) were prepared by ultrasonic vibration and used to investigate nanoparticle concentration on pressure drop of gas-liquid two-phase boiling flow of a nanorefrigerant in micro channels. A micro heat exchanger was fabricated by direct metal laser sintering (DMLS) with designed capacity of system pressure at 176 kPa and inlet temperature at 40℃. At conditions of heat flux 21.2-38.2 kW·m-2 and mass flow rate 183.13-457.83 kg·m-2·s-1
the experimental results show that the nanoparticle concentration had significant impact on pressure drop of Al2O3/R141b nanoparticle coolant boiling flow in micro channels and the pressure drop decreased with the increase of nanoparticle concentration. After added Al2O3 nanoparticles to pure R141b coolant
pressure drop of the pure refrigerant in micro channels was reduced by 5.5%-32.6% depending on mass faction of nanoparticles. Scanning electron microscopy (SEM) and static contact angle measurement revealed that deposition of some Al2O3 nanoparticles on the microchannel surface increased surface wettability
which might lower pressure drop of Al2O3/R141b upon increase of nanoparticle concentration. Considered three classic pressure drop models and correlations of Qu-Mudawar's and Zhang's for gas-liquid two-phase boiling flow
a revised correlation was developed that 85% of the experimental data points on pressure drop were fallen within a ±15% range of model calculation. The revised correlation can effectively predict the experimental results under these conditions as supported by small MAE number of 11.7%
which was relative deviation between experimental results and revised model predictions.