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Prediction of Slipping Accidents Usi...

Iraqi, Arian.

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Prediction of Slipping Accidents Using Biomechanical and Traction Analysis of Footwear Outsole Design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Prediction of Slipping Accidents Using Biomechanical and Traction Analysis of Footwear Outsole Design./
作者:	Iraqi, Arian.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	141 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-10, Section: B.
Contained By:	Dissertations Abstracts International80-10B.
標題:	Occupational safety. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13872122
ISBN:	9781392042939

Prediction of Slipping Accidents Using Biomechanical and Traction Analysis of Footwear Outsole Design.
Iraqi, Arian.

Prediction of Slipping Accidents Using Biomechanical and Traction Analysis of Footwear Outsole Design. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 141 p.

Source: Dissertations Abstracts International, Volume: 80-10, Section: B.

Thesis (Ph.D.)--University of Pittsburgh, 2018.

This item must not be sold to any third party vendors.

Slip-initiated falls due to insufficient traction are a major contributor to occupational injuries. Footwear interventions have a significant potential to mitigate slipping accidents. Unfortunately, performance of the footwear used in these interventions is variable and there is a paucity of empirical evidence supporting the validity of current methods for assessing footwear traction. Furthermore, footwear traction testing methods are expensive and require expertise, which may limit their use. These limitations may guide footwear designers toward suboptimal footwear and create barriers for safety managers to assess and identify appropriate footwear. The goal of this dissertation was to (1) guide the development of valid traction testing methods and (2) create tread assessment methods that are inexpensive and require minimal expertise. The ability of footwear traction tests under different biomechanical parameters (normal force, shoe-floor angle, and sliding speed) to predict slip outcomes were assessed based on human exposures to slippery surfaces. The combination of 250 N normal force and 17° shoe-floor angle best predicted slip risk during gait experiments. Biomechanical analysis of various shoes during human slipping events were performed to guide shoe traction measurements for additional improvements. The findings revealed that the normal force (26.7 %BW, 179 N), shoe-floor angle (22.1°) and contact time (0.02 s) at slip initiation were significantly different from current footwear traction testing standard methods (400 and 500 N, 7º, 0.10-0.30 s). Thus, current methods may need to utilize lower normal forces, larger shoe-floor angles and shorter contact duration to further improve slip risk prediction by mimicking the shoe dynamics at slip initiation. A tread assessment model was developed to predict footwear traction based on outsole design features. The statistical model predicted 88% of variation in traction using contact area, heel shape, shape factor and material hardness while controlling for the floor surface in the presence of canola oil. Safety practitioners can use this information to select shoes with high slip-resistant performance in cases where footwear traction testing apparatuses are not readily available. The findings from this dissertation may reduce slipping accidents by improving the quality and accessibility of shoe traction assessment methods.

ISBN: 9781392042939Subjects--Topical Terms:

3172193
Occupational safety.
Subjects--Index Terms:

Coefficient of friction

Prediction of Slipping Accidents Using Biomechanical and Traction Analysis of Footwear Outsole Design.
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520 $a Slip-initiated falls due to insufficient traction are a major contributor to occupational injuries. Footwear interventions have a significant potential to mitigate slipping accidents. Unfortunately, performance of the footwear used in these interventions is variable and there is a paucity of empirical evidence supporting the validity of current methods for assessing footwear traction. Furthermore, footwear traction testing methods are expensive and require expertise, which may limit their use. These limitations may guide footwear designers toward suboptimal footwear and create barriers for safety managers to assess and identify appropriate footwear. The goal of this dissertation was to (1) guide the development of valid traction testing methods and (2) create tread assessment methods that are inexpensive and require minimal expertise. The ability of footwear traction tests under different biomechanical parameters (normal force, shoe-floor angle, and sliding speed) to predict slip outcomes were assessed based on human exposures to slippery surfaces. The combination of 250 N normal force and 17° shoe-floor angle best predicted slip risk during gait experiments. Biomechanical analysis of various shoes during human slipping events were performed to guide shoe traction measurements for additional improvements. The findings revealed that the normal force (26.7 %BW, 179 N), shoe-floor angle (22.1°) and contact time (0.02 s) at slip initiation were significantly different from current footwear traction testing standard methods (400 and 500 N, 7º, 0.10-0.30 s). Thus, current methods may need to utilize lower normal forces, larger shoe-floor angles and shorter contact duration to further improve slip risk prediction by mimicking the shoe dynamics at slip initiation. A tread assessment model was developed to predict footwear traction based on outsole design features. The statistical model predicted 88% of variation in traction using contact area, heel shape, shape factor and material hardness while controlling for the floor surface in the presence of canola oil. Safety practitioners can use this information to select shoes with high slip-resistant performance in cases where footwear traction testing apparatuses are not readily available. The findings from this dissertation may reduce slipping accidents by improving the quality and accessibility of shoe traction assessment methods.
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