A many-body dissipative particle dynamics with energy conservation study of droplets icing on microstructure surfaces

Abstract

Droplets icing has important applications in real life. The icing process of droplets on microstructure is explored based on the MDPDE method in this study. Firstly, the correctness of the heat transfer model was verified by one-dimensional heat conduction simulation, and then the feasibility of the phase change model was verified by investigating the icing process of droplets. The influence of cold surface temperature, droplet volume and contact angle on freezing time of droplets was discussed, and it was found that the temperature of cold surfaces had a greater effect on freezing. We finally explored the influence of different microstructure surfaces on the icing of droplets, and results showed that the presence of microstructures greatly enhanced the anti-icing effect of the surface. In our research, the contact angle is a relatively large factor affecting the icing of droplets. In addition, it was discovered that the droplet had the strongest ability to delay freezing on the surface of triangle microstructures with a contact angle of 157.1°.

Flow Reduction in Pore Networks of Packed Silica Nanoparticles: Insights from Mesoscopic Fluid Models

“…As a result of coarse-graining from MD, the critical time step required in DPD models is several orders of magnitude larger than their MD counterparts, thus permitting sampling of both length and time scales equivalent to those experimentally measurable. In DPD, simulations of multiphase fluid dynamics (including fluid–fluid and fluid–solid interactions) are made possible by several multiphase-enabled DPD models. − Among the DPD model variants, the many-body DPD (mDPD) model is a prominent candidate for mesoscopic simulations of fluid flow in nanoporous materials. − The mDPD model can reproduce the compressibility of real liquid fluids as a function of pressure by considering the many-body interactions ,− and has been applied for qualitative studies of surface tension, contact angle characterization, , multiphase flow in microchannels, − droplets impact on surfaces, − and nanocapillaries . A recent review of mDPD on its theories and applications is reported in Zhao et al…”

Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

“…In DPD, simulations of multiphase/component flow are enabled by several model variants, 19,[36][37][38]67,72,76 among which the many-body DPD (mDPD) model 76 is prominent for mesoscopic simulations of multicomponent flow in nanoporous media. 79,80 The mDPD model can predict the compressibility of real liquids as a function of pressure by considering the manybody interactions 51,68,69,71,76 and has been applied in the studies of surface tension, 15 contact angle, 33,83 multiphase flow in microchannels, 4−6 droplets on surfaces, 10,30,73,74 and nanocapillaries. 8 A review of mDPD was recently reported by Zhao et al 88 Despite the many proven capabilities of mDPD, it has been a challenge for mDPD to accurately simulate the static and dynamic properties of real fluids at the same time.…”

“…The critical time step size in DPD is thus several orders of magnitude larger than that in MD and allows for the sampling of length and time scales to be much larger. In DPD, simulations of multiphase/component flow are enabled by several model variants, ,− ,,, among which the many-body DPD (mDPD) model is prominent for mesoscopic simulations of multicomponent flow in nanoporous media. , The mDPD model can predict the compressibility of real liquids as a function of pressure by considering the many-body interactions ,,,, and has been applied in the studies of surface tension, contact angle, , multiphase flow in microchannels, − droplets on surfaces, ,,, and nanocapillaries . A review of mDPD was recently reported by Zhao et al…”