Prediction of slip resistance in climbing systems

Abstract

The objective of this study was to develop a predictive model describing the slip resistance of various climbing surfaces. In a four-factor experiment, seven commonly used metal grating step surfaces were evaluated, along with four types of shoe soles (crepe, leather, ribbed-rubber, and oil-resistant-rubber); three contaminant conditions (dry, wet-water, and diesel fuel); and direction of force application. The results showed that the available slip resistance coefficients (ASRC) varied primarily as a function of sole material and contaminants. This result and the significant interactions between sole and step surfaces suggest that the appropriate selection of shoe soles and control of contaminants may be the most effective way of attaining adequate ASRC values. A predictive equation was developed using multiple regression which described the evaluated conditions with binary indicator variables. To increase the equation's applicability, the step surfaces were described in terms of generic features such as: painted vs. bare metal surface; ring vs. point protrusions; edge orientation; contact area, and protrusion height gradient. The equation explained 89% of the variance in the original data. In a validation study, the equation explained 80% of the variance in slip resistance for a new step surface under the original set of sole, contaminant, and directionality conditions.