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contributor authorGu, Huiqing
contributor authorJiao, Li
contributor authorYan, Pei
contributor authorGuo, Zhibo
contributor authorQiu, Tianyang
contributor authorWang, Xibin
date accessioned2023-08-16T18:03:49Z
date available2023-08-16T18:03:49Z
date copyright12/26/2022 12:00:00 AM
date issued2022
identifier issn0742-4787
identifier othertrib_145_4_041702.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4291332
description abstractSurface skewness and kurtosis are two crucial topography property indexes that greatly influence the functional performance of the machined surface. This paper proposes a modified model of stress concentration factor (SCF), which integrates these two surface texture parameters with the well-known standard surface roughness parameters (Arola's model). The relative weight of positive and negative heights of the surface is considered to describe the influence of the shape of the peaks and valleys on the stress concentration of the surface profile for the first time, meanwhile, without losing the effect of the standard surface roughness parameters. The performance of the modified model is studied by comparing it with the other two models involving various aspects of the functional performance of machined surfaces, including fatigue life, wear resistance, fretting crack nucleation, and initiation behaviors, as well as the surface bearing capability. The results indicate that by accounting for the surface skewness and kurtosis parameters, the modified model is more suitable for evaluating the SCF of machined surfaces, appropriately describing the correlation between surface texture and fatigue life and achieving a good prediction of fatigue life compared with the experimental results.
publisherThe American Society of Mechanical Engineers (ASME)
titleA Surface Skewness and Kurtosis Integrated Stress Concentration Factor Model
typeJournal Paper
journal volume145
journal issue4
journal titleJournal of Tribology
identifier doi10.1115/1.4056455
journal fristpage41702-1
journal lastpage41702-12
page12
treeJournal of Tribology:;2022:;volume( 145 ):;issue: 004
contenttypeFulltext


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