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

项目摘要 每年有超过140，000名工人因跌倒受伤，造成严重的人类痛苦， 100亿美元的工人赔偿金。大约一半的职业性福尔斯跌倒是由 下滑一个未充分探索的途径，以防止这些滑倒事件是设计地板， 高摩擦性能的工作场所。高摩擦地板可防止滑倒。 不幸的是，目前表征地板表面形貌的方法无法预测摩擦 #21453;，限制了这一领域的创新。为了促进高摩擦地板的创新， 需要提高对导致摩擦的地板因素的科学认识。我们的初步 研究和现有文献表明，小尺度形貌（1 nm至1 µm尺度的特征） 这对于预测地板性能至关重要，但使用常规表征技术是不可测量的。 这个R21项目的目的是测量这些小尺度的地面地形，并利用它们 开发一个基于力学的摩擦预测模型。这项研究是创新的，因为它将采用 新颖的实验方法和分析技术从未应用于地板表面， 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 性能，其中先前的研究仅依赖于经验相关性。拟议的研究将是 通过两个目标实现： 目的1：量化鞋-地板摩擦性能对小尺度地形的依赖性。这一目标 将研究小规模地形的能力，以解释鞋地板摩擦性能的变化， 无法用现有的测量技术来解释。然后我们将测试第一个假设：假设 1：考虑全范围尺度的粗糙度参数将提高我们预测COF值的能力 与仅使用触针轮廓术的那些相比。 目的2：建立基于多尺度的预测力学模型 表面形貌在这个目标中，我们将开发和验证一个多尺度有限元模型， 粘弹性对所有长度尺度上的摩擦的贡献。我们将检验第二个假设：假设2： 基于力学的多尺度地形模型将更准确地预测鞋底摩擦 与传统方法相比，即，基于触针轮廓术的统计模型。 这项研究预计将导致基础知识和建模工具，以优化高摩擦 工作场所的地板。与一个行业贸易组织，北美瓷砖理事会（TCNA）合作， 研究将通过指导以证据为基础的高摩擦地板的开发来实现影响， 工作场所。因此，拟议的研究预计将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.