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首页> 外文期刊>International Journal of Heat and Mass Transfer >Mass, momentum, and energy transfer in supersonic aerosol deposition processes
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Mass, momentum, and energy transfer in supersonic aerosol deposition processes

机译:超音速气溶胶沉积过程中的质量,动量和能量转移

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Aerosol deposition (AD) can lead to the formation of dense coatings via deposition of particles from a gas flow; in AD the aerosol is passed through a converging-diverging nozzle, facilitating inertial particle impaction on a desired substrate at supersonic particle velocities. Unique from thermal spray methods, AD can be applied near room temperature and unique from cold spray, in AD the aerosol is typically at atmospheric pressure upstream of the nozzle. Though AD has been successfully demonstrated previously, a number of aspects related to particle motion in AD systems remain poorly understood. In this work, we simulated compressible flow field profiles and particle trajectories for typical AD working conditions for a slit type converging-diverging nozzle with a planar substrate. In examining the fluid flow profile, we show that the velocity and pressure profiles, as well as the shock structure are sensitive to the upstream and downstream operating pressures of the nozzle. These ultimately affect particle impaction speed. Importantly, in AD, the particle drag regime is dynamic; both particle Knudsen numbers and Mach numbers can vary by orders of magnitude. To aid particle trajectory simulations, we trained a neural network to predict the drag force on the particles based on existing experimental data, theoretical limits, and new direct simulation Monte Carlo (DMSC) results. The neural network based drag law, which depends upon both Mach and Knudsen numbers, shows better agreement with the DSMC simulation data than preexisting correlations. With it, particle trajectory simulation results reveal that for a given particle density, there exists an optimal particle diameter to maximize particle impaction speed. We also find that in AD particles undergo size dependent inertial focusing, i.e. there is a particular particle diameter where the particle deposition linewidth is minimized. Particles smaller than this diameter are underfocused, and particles larger than this are overfocused, and hence have larger deposition linewidths in both cases. Using trajectory simulations, we additionally developed a framework that can be used to evaluate the position-dependent mass, momentum and kinetic energy fluxes to the deposition substrate for any aerosol size distribution function upstream of the nozzle. It is shown for typical aerosol concentrations achievable in the laboratory, the kinetic energy flux can approach a magnitude normally observed in convective heat transfer with phase change, hence translational kinetic energy to thermal energy transfer in AD is likely a key contributor to the formation of dense coatings. (C) 2018 Elsevier Ltd. All rights reserved.
机译:气溶胶沉积(AD)会通过气流中的颗粒沉积而导致形成致密涂层。在公元AD中,气雾剂通过会聚-发散喷嘴,以惯性粒子速度促进惯性粒子撞击在所需基材上。 AD具有热喷涂法的独特之处,可在室温附近应用,AD具有冷喷涂的独特性,在AD中,气溶胶通常处于喷嘴上游的大气压下。尽管AD已经在以前得到了成功的证明,但是与AD系统中粒子运动有关的许多方面仍然知之甚少。在这项工作中,我们模拟了带有平面基板的狭缝型会聚-发散喷嘴在典型AD工作条件下的可压缩流场分布和颗粒轨迹。在检查流体流动曲线时,我们表明速度和压力曲线以及激波结构对喷嘴的上游和下游工作压力敏感。这些最终会影响粒子碰撞速度。重要的是,在AD中,粒子阻力机制是动态的。 Knudsen数和Mach数都可以按数量级变化。为了帮助进行粒子轨迹模拟,我们训练了一个神经网络以根据现有的实验数据,理论极限以及新的直接模拟蒙特卡洛(DMSC)结果来预测粒子上的阻力。基于神经网络的阻力定律(同时依赖于Mach和Knudsen数)显示出与DSMC仿真数据更好的一致性,而不是预先存在的相关性。有了它,粒子轨迹模拟结果表明,对于给定的粒子密度,存在一个最佳的粒子直径,以最大化粒子撞击速度。我们还发现,在AD中,颗粒经历取决于尺寸的惯性聚焦,即,存在特定的颗粒直径,其中颗粒沉积线宽最小。小于此直径的粒子未聚焦,而大于此直径的粒子则过度聚焦,因此在两种情况下均具有较大的沉积线宽。使用轨迹模拟,我们还开发了一个框架,该框架可用于评估到喷嘴上游的任何气溶胶尺寸分布函数的位置相关的质量,动量和动能通量到沉积基质。结果表明,对于实验室中可达到的典型气溶胶浓度,动能通量可以接近对流传热中相变时通常观察到的幅度,因此,平移动能向热能传递的平移动能可能是致密物形成的关键因素。涂料。 (C)2018 Elsevier Ltd.保留所有权利。

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