Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia.
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, Australia.
Comput Biol Med. 2022 Sep;148:105904. doi: 10.1016/j.compbiomed.2022.105904. Epub 2022 Jul 20.
Cartilage surface roughness has significant implications on joint lubrication. However, the effects of the variability in surface roughness in different directions (especially in horizontal direction) in mixed-mode lubrication have not been fully investigated and relevant research work in this field is limited. This study presents a probabilistic numerical approach to investigate the influence of variability and uncertainty of Root-Mean-Square (RMS) roughness heights (vertical roughness) and roughness correlation lengths (horizontal roughness) on cartilage lubrication.
The synthetic surface topographies with typical ranges of vertical and horizontal roughness characteristics were firstly input to a coupled cartilage contact model. A response surface was then constructed using the input roughness parameters and the output coefficient of friction (CoF). Finally, a large number of independent or correlated roughness samples were generated for computing the probability of mixed-mode lubrication failure (PoF), which was defined as CoF > 0.27 (corresponding to a 90% loss of fluid support in the contact interface).
Both independent RMS roughness heights and correlation lengths are correlated positively with CoF. This indicates that the increase of the vertical surface roughness could exacerbate cartilage wear, whereas increasing surface roughness in horizontal direction (i.e., reducing correlation lengths) could retain gap fluid that aids mixed-mode lubrication. Importantly, it shows that CoF is dominant by RMS roughness height. The uncertainty in the independent correlation lengths may lead to the underestimation of PoF. By simulating osteoarthritic surface roughness with a strong correlation between RMS roughness heights and correlation lengths, the value of PoF could reach 70-99%.
This study highlights the significance of incorporating the mutual relations between the surface roughness in vertical and horizontal directions into research, and the findings could potentially contribute to the design of biomimetic cartilage surfaces for the treatment of osteoarthritis.
软骨表面粗糙度对关节润滑有重要影响。然而,混合润滑模式下不同方向(尤其是水平方向)表面粗糙度变化的影响尚未得到充分研究,该领域的相关研究工作有限。本研究提出了一种概率数值方法,研究均方根(RMS)粗糙度高度(垂直粗糙度)和粗糙度相关长度(水平粗糙度)的可变性和不确定性对软骨润滑的影响。
首先将具有典型垂直和水平粗糙度特征范围的合成表面形貌输入到耦合软骨接触模型中。然后使用输入的粗糙度参数和输出摩擦系数(CoF)构建响应面。最后,生成大量独立或相关的粗糙度样本,以计算混合模式润滑失效的概率(PoF),定义为 CoF>0.27(对应于接触界面中 90%的流体支撑损失)。
独立 RMS 粗糙度高度和相关长度均与 CoF 呈正相关。这表明垂直表面粗糙度的增加会加剧软骨磨损,而增加水平方向的表面粗糙度(即减小相关长度)可以保留有助于混合模式润滑的间隙流体。重要的是,它表明 CoF 主要由 RMS 粗糙度高度决定。独立相关长度的不确定性可能导致 PoF 的低估。通过模拟 RMS 粗糙度高度和相关长度之间具有强相关性的骨关节炎表面粗糙度,PoF 的值可达 70-99%。
本研究强调了将垂直和水平方向表面粗糙度之间的相互关系纳入研究的重要性,研究结果可能有助于设计仿生软骨表面以治疗骨关节炎。