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arXiv 2602.16420physics.flu-dynphysics.comp-ph
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结合动态和运动学验证的液滴-壁碰撞建模

Combined dynamic-kinematic validation of droplet-wall impact modeling

Moscow Aviation Institute (National Research University)(莫斯科航空学院(国立研究型大学));School of Energy and Power Engineering, Tomsk Polytechnic University(托木斯克理工大学能源与动力工程学院);Center for Materials Technologies, Skolkovo Institute of Science and Technology(斯科尔科沃科学技术研究院材料技术研究中心)

Dmitry Zharikov, Maxim Piskunov, Dmitry Kolomenskiy

AI总结:

本文提出结合动态和运动学指标的液滴碰撞模型,通过比较两种接触角方法,改进液滴扩展和回缩预测,并引入$(β_{max},\,Ca_{char})$图关联扩展特性与内部流体动力学。

摘要:

许多数值研究仅使用最大扩展直径来验证液滴碰撞壁的模型,但这一指标单独无法确保液滴动力学的正确性。我们提出了一个结合动态接触角(DCA)模型,该模型融合了广义霍夫曼-沃伊诺夫-塔纳定律的几何准确性与基于霍夫曼函数的运动学一致性,从而改进了液滴扩展和回缩的预测。我们模拟了水-甘油液滴在蓝宝石玻璃上的碰撞,Weber数为20至250,并评估了两种接触角模型。通过Python中的SciPy处理模拟的径向速度场,并与粒子图像测速法(PIV)测量的液滴扩展纵向截面进行比较。基于霍夫曼函数的模型捕捉了液滴运动学的主要趋势,并提供了更一致的回缩动力学。广义霍夫曼-沃伊诺夫-塔纳定律在最大扩展直径方面误差不超过7%。然而,在回缩过程中,其径向速度的中位绝对误差是霍夫曼函数解的三倍。即使最大扩展被再现,平均径向速度和扩展速度也可能与实验趋势不同。这些发现支持结合几何和运动学指标的验证,并推动了联合模型用于预测扩展和回缩。使用最大扩展因子$β_{max}$作为最大扩展直径与初始液滴直径的比值,以及从300微米上方基底的平均内部水平速度定义的特征毛细数$Ca_{char}$,我们引入了一个$(β_{max},\,Ca_{char})$图来关联扩展特性与内部流体动力学。我们假设,给定足够的数据,接触线几何可能用于估计内部运动学。

英文摘要:

Many numerical studies validate droplet wall impact using only maximum spreading diameter, yet this metric alone cannot ensure correct droplet dynamics. We present a combined dynamic contact angle (DCA) model that merges the geometric accuracy of the generalized Hoffman-Voinov-Tanner law with the kinematic consistency of a Hoffman function-based approach, improving predictions of droplet spreading and receding. We simulate water-glycerol droplet impact on sapphire glass at Weber numbers 20 -- 250 and assess both contact angle formulations. Simulated radial velocity fields are processed in Python using SciPy and compared with Particle Image Velocimetry measurements in the longitudinal section of the spreading droplet. The Hoffman function-based model captures the main droplet kinematic trends and provides more consistent receding dynamics. The generalized Hoffman-Voinov-Tanner law matches the maximum spreading diameter within 7%. However, during receding, it shows a median absolute error in radial velocity up to three times higher than that of the Hoffman function-based solution. Average radial velocity and spreading velocity can differ from experimental trends even when maximum spreading is reproduced. These findings support validation combining geometric and kinematic metrics and motivate the combined model for predicting spreading and receding. Using the maximum spreading factor $β_{max}$ as the ratio of the maximum spreading diameter over the initial droplet diameter and the characteristic capillary number $Ca_{char}$ defined from the mean internal horizontal velocity at 300 micrometer above the substrate, we introduce a $(β_{max},\,Ca_{char})$ diagram to relate spreading characteristics to internal flow dynamics. We hypothesize that, given sufficient data, the contact-line geometry may be used to estimate internal kinematics.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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