The Surface Roughness of a Rubber Soling Material Determines the Coefficient of Friction on Water-Lubricated Surfaces

Research on Slip Resistance Measurements<br>—A New Challenge

“…Kim et al 6) examined this aspect from a wear point of view and found that changes in the DFC results were largely caused by wear developments of the heel surfaces. Manning et al 14) also showed an interesting result that extended wear on smooth floors could cause polishing and a considerable fall in COF results. In this sense, if the surface characteristics of shoe soles/heels and floors and their interactions could be quantitatively measured and analysed, then our understanding on this complex issue of friction and wear mechanics and mechanisms would be considerably enhanced.…”

“…New conceptual foundations for characterizing the slip resistance properties should be based on thorough understanding of fundamental mechanics and mechanisms of tribological characteristics between the shoes and floors. Because surface topographies of the shoes and floors are largely modified throughout the course of repetitive contact-sliding friction processes, this may considerably affect overall friction and wear behaviours and be one of the most important factors on the slip resistance properties [4][5][6][8][9][10][11][12][13][14][15][16][17] . While controversies around the friction measurement for slipperiness assessment still remain 25) , a tribological classification may provide an objective alternative to overcome the current problems of slip resistance evaluations.…”

Slip Safety Risk Analysis of Surface Properties by Determining Coefficients of Friction (COF) of Natural Stones

“…Çizelge 1. Çıplak ayakla gezilen ıslak bölgelerin kaymayı önleme özelliğinin belirlenme testi sonuçlarının sınıflandırılması [20]. …”

Preferred surface microscopic geometric features on floors as potential interventions for slip and fall accidents on liquid contaminated surfaces

“…A typical surface roughness profile. Table 1 The definitions of surface roughness parameters R 3y maximum height of third highest peak to third lowest valley in each cut-off length R 3z mean height from third highest peak to third lowest valley in each cut-off length R a arithmetical average of surface heights or the center line average of surface heights R c correlation distance calculated from the autocorrelation coefficient of surface heights R k kernel roughness depth R ku kurtosis of surface heights R p maximum height of the profile above the mean line within the assessed length R pk reduced peak height R pm average of the maximum height above the mean line in each cut-off length R q root mean square of surface heights R sk skewness of surface heights R t maximum peak to valley height in the assessed length R tm average of peak to valley height in each cut-off length R v maximum depth of the profile below the mean line within the assessed length R vk reduced trough depth R y maximum of peak to valley in all cut-off lengths R z average height difference between five highest peaks and five lowest valleys within each cut-off length S mean spacing of adjacent local peaks S m mean spacing between profile peaks at the mean line E q root mean square measure of spatial wavelength D a arithmetical mean of surface slope D q root mean square of surface slope were measured (Grönqvist, Roine, Korhonen, & Rahikainen, 1990;Harris & Shaw, 1988;Jung & Reidiger, 1982;Manning & Jones, 1994;Manning & Jones, 2001;Manning, Jones, & Bruce, 1990;Manning, Jones, & Bruce, 1991;Manning, Jones, Rowland, & Roff, 1998;Rowland, Jones, & Manning, 1996). In some studies, several surface roughness parameters were used (Kim & Smith, 2000;Kim, Smith, & Nagata, 2001;Lloyd & Stevenson, 1992), but no reason was given to explain why they were chosen.…”