Reducing slip-and-fall accidents in the workplace: Role of small-scale roughness of floor surfaces to improve friction

项目摘要 与跌倒相关的伤害每年给超过14万名工人带来负担，造成巨大的人类痛苦和 100亿美元的工人补偿的经济成本。大约一半的职业性跌倒是由 滑倒了。防止这些滑倒事件的一种未被探索的方法是为 具有高摩擦性能的工作场所。高摩擦地板可防止导致跌倒的滑动事件。 不幸的是，目前表征地板表面形貌的方法不能预测摩擦力。 性能，限制了这一领域的创新。为了催化高摩擦地板的创新，有一种 需要改进对地板摩擦因素的科学理解。我们的预赛 研究和现有文献表明，小尺度地形(1纳米到1微米尺度的特征)是 对于预测地板性能至关重要，但无法使用传统的表征技术进行测量。 R21项目的目的是测量这些小尺度的地面表面形貌，并使用它们 建立基于力学的摩擦力预测模型。这项研究具有创新性，因为它将利用 新颖的实验方法和分析技术，从未应用于地板表面，以及 因为它将开发一个基于力学的模型来预测地板结构和摩擦力之间的关系 绩效，以前的研究完全依赖于经验相关性。拟议的研究将是 通过两个目标实现： 目的1：量化小尺度地形对鞋底摩擦性能的影响。这一目标 将研究小尺度地形解释鞋底摩擦性能变化的能力 无法用目前的测量技术来解释。然后我们将检验第一个假设：假设 1：考虑全尺度范围的粗糙度参数将提高我们预测COF值的能力 与仅使用光笔轮廓术的人相比。 目的2：建立基于多尺度的鞋底摩擦预测力学模型 表面地形。为此，我们将开发和验证一个多尺度有限元模型，该模型捕获了 粘弹性对所有长度尺度上的摩擦力的贡献。我们将检验第二个假设：假设2： 使用多尺度地形的力学模型将更准确地预测鞋底摩擦 与传统方法相比，即基于光笔轮廓术的统计模型。 这项研究有望为优化高摩擦力提供基础知识和建模工具 工作场所的地板。与行业贸易组织北美瓷砖委员会(TCNA)合作，这 研究将通过指导高摩擦地板的循证发展来实现影响 工作场所。因此，拟议的研究有望在改善工作场所安全方面产生影响。

Project Summary Fall-related injuries burden over 140,000 workers annually, causing significant human suffering and an economic cost of $10 billion in Workers' Compensation. Approximately half of occupational falls are caused by slipping. An under-explored pathway to preventing these slip-and-fall events is to design flooring for workplaces with high friction performance. High-friction flooring prevents the slip events that lead to a fall. Unfortunately, current methods to characterize floor-surface topography are unable to predict friction performance, limiting innovation in this area. In order to catalyze innovation in high-friction flooring, there is a need for improved scientific understanding of the flooring factors that contribute to friction. Our preliminary studies and existing literature suggest that small-scale topography (features at the 1-nm to 1-µm scale) is critical for predicting floor performance, but is not measurable using conventional characterization techniques. The purpose of this R21 project is to measure these small-scales of floor-surface topography, and to use them to develop a mechanics-based predictive model for friction. This research is innovative because it will employ novel experimental methods and analysis techniques that have never been applied to flooring surfaces, and because it will develop a mechanics-based model to predict the relationship between floor structure and friction performance, where prior research has relied solely on empirical correlations. The proposed research will be accomplished through two Aims: Aim 1: Quantify the dependence of shoe-floor friction performance on small-scale topography. This Aim will investigate the ability of small-scale topography to explain variations in shoe-floor friction performance that cannot be explained using current measurement techniques. Then we will test the first hypothesis: Hypothesis 1: Roughness parameters that consider the full range of scales will improve our ability to predict COF values compared with those using just stylus profilometry. Aim 2: Establish a predictive mechanics-based model for shoe-floor friction based on multiscale surface topography. In this Aim, we will develop and validate a multiscale finite element model that captures viscoelastic contributions to friction across all length scales. We will test the second hypothesis: Hypothesis 2: A mechanics-based model using multiscale topography will more accurately predict shoe-floor friction compared with conventional approaches, i.e., statistical models based on stylus profilometry. This research is expected to lead to foundational knowledge and a modeling tool for optimizing high-friction flooring in workplaces. Working with an industry trade group, the Tile Council of North America (TCNA), this research will achieve impact by guiding the evidence-based development of high-friction flooring for workplaces. Thus, the proposed research is expected to achieve impact in improving workplace safety.