IJPEM-GT
Convective Heat Transfer Coefficient Model Under Nanofluid Minimum
Quantity Lubrication Coupled with Cryogenic Air Grinding Ti–6Al–4V
Changhe Li/Qingdao University of Technology
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Keywords : Grinding,
Nanofluid minimum quantity lubrication,
Vortex tube,
Cold air fraction,
Convective heat transfer coefficient,
Temperature field
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Under the threat of serious environmental pollution and resource waste, sustainable
development and green manufacturing have gradually become a new development trend. A
new environmentally sustainable approach, namely, cryogenic air nanofluid minimum
quantity lubrication (CNMQL), is proposed considering the unfavorable lubricating
characteristic of cryogenic air (CA) and the deficient cooling performance of
minimum quantity lubrication (MQL). However, the heat transfer mechanism of vortex
tube cold air fraction by CNMQL remains unclear. The cold air fraction of vortex
tubes influences the boiling heat transfer state and cooling heat transfer
performance of nanofluids during the grinding process. Thus, a convective heat
transfer coefficient model was established based on the theory of boiling heat
transfer and conduction, and the numerical simulation of finite difference and
temperature field in the grinding zone under different vortex tube cold air
fractions was conducted. Simulation results demonstrated that the highest
temperature initially declines and then rises with increasing cold air fraction.
Afterward, this temperature reaches the lowest peak (192.7 °C) when the cold air
fraction is 0.35. Experimental verification was conducted with Ti–6Al–4V to verify
the convective heat transfer coefficient model. The results concluded that the low
specific grinding energy (66.03 J/mm3), high viscosity (267.8 cP), and large contact
angle (54.01°) of nanofluids were obtained when the cold air fraction was 0.35.
Meanwhile, the lowest temperature of the grinding zone was obtained (183.9 °C).
Furthermore, the experimental results were consistent with the theoretical analysis,
thereby verifying the reliability of the simulation model.
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