2019
DOI: 10.3390/ceramics2010013
|View full text |Cite
|
Sign up to set email alerts
|

Roughness Effect in Micropitting and Rolling Contact Fatigue of Silicon Nitride

Abstract: An experimental analysis of the role of surface roughness parameters on micropitting and the succeeding rolling contact fatigue (RCF) of silicon nitride against AISI 52100 steel under lubricated conditions was performed. In accelerated fatigue tests using a four-ball tester, the arithmetic mean, root mean square, and peak-to-valley roughnesses of silicon nitride surfaces varied, while the roughness of the steel surface was unchanged. The correlation between the fatigue life and roughness parameters for silicon… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 25 publications
0
1
0
Order By: Relevance
“…All tests were performed for a total of 10 × 10 6 rotation cycles at a constant load of 1960 N with the maximum Hertz contact pressure of 2.1 GPa. 2.1 Surface roughness Surface roughness is one of the key parameters influencing surface damage in low Λ conditions [24][25][26][27]. Each test bearing consists of a combination of raceways with roughness ranging from 0.02 to 0.06 µm and steel balls with roughness up to 0.60 µm in the mean-square root (RMS) which is expressed as "Rq".…”
Section: Experimental Methodologymentioning
confidence: 99%
“…All tests were performed for a total of 10 × 10 6 rotation cycles at a constant load of 1960 N with the maximum Hertz contact pressure of 2.1 GPa. 2.1 Surface roughness Surface roughness is one of the key parameters influencing surface damage in low Λ conditions [24][25][26][27]. Each test bearing consists of a combination of raceways with roughness ranging from 0.02 to 0.06 µm and steel balls with roughness up to 0.60 µm in the mean-square root (RMS) which is expressed as "Rq".…”
Section: Experimental Methodologymentioning
confidence: 99%