Wang Chao, Bonyadi Shabnam Z, Grün Florian, Pinter Gerald, Hausberger Andreas, Dunn Alison C
Polymer Competence Center Leoben GmbH, Roseggerstraße 12, 8700 Leoben, Austria.
Department of Mechanical Science & Engineering, University of Illinois at Urbana-Champaign, 1206 W. Green St. MC 244, Urbana, IL 61801, USA.
Materials (Basel). 2020 Oct 16;13(20):4615. doi: 10.3390/ma13204615.
Stick-slip friction of elastomers arises due to adhesion, high local strains, surface features, and viscous dissipation. In situ techniques connecting the real contact area to interfacial forces can reveal the contact evolution of a rough elastomer surface leading up to gross slip, as well as provide high-resolution dynamic contact areas for improving current slip models. Samples with rough surfaces were produced by the same manufacturing processes as machined seals. In this work, a machined fluoroelastomer (FKM) hemisphere was slid against glass, and the stick-slip behavior was captured optically in situ. The influence of sliding velocity on sliding behavior was studied over a range of speeds from 1 µm/s to 100 µm/s. The real contact area was measured from image sequences thresholded using Otsu's method. The motion of the pinned region was delineated with a machine learning scheme. The first result is that, within the macroscale sticking, or pinned phase, local pinned and partial slip regions were observed and modeled as a combined contact with contributions to friction by both regions. As a second result, we identified a critical velocity below which the stick-slip motion converted from high frequency with low amplitude to low frequency with high amplitude. This study on the sliding behavior of a viscoelastic machined elastomer demonstrates a multi-technique approach which reveals precise changes in contact area before and during pinning and slip.
弹性体的粘滑摩擦是由粘附、高局部应变、表面特征和粘性耗散引起的。将实际接触面积与界面力联系起来的原位技术可以揭示粗糙弹性体表面直至整体滑动的接触演变,还能提供高分辨率的动态接触面积,以改进当前的滑动模型。具有粗糙表面的样品是通过与加工密封件相同的制造工艺生产的。在这项工作中,将一个加工过的氟橡胶(FKM)半球体在玻璃上滑动,并通过光学原位捕捉其粘滑行为。在1 µm/s至100 µm/s的速度范围内研究了滑动速度对滑动行为的影响。通过使用大津法进行阈值处理的图像序列来测量实际接触面积。用机器学习方案描绘固定区域的运动。第一个结果是,在宏观粘附或固定阶段内,观察到局部固定和部分滑动区域,并将其建模为一个对摩擦有贡献的组合接触。第二个结果是,我们确定了一个临界速度,低于该速度时,粘滑运动从高频低幅转变为低频高幅。这项对粘弹性加工弹性体滑动行为的研究展示了一种多技术方法,该方法揭示了固定和滑动之前及期间接触面积的精确变化。