Mesoscale Numerical Modeling for Predicting Wear Debris Generation View Full Text


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Article Info

DATE

2019-06

AUTHORS

Tongyang Li, Jian Shi, Shaoping Wang, Enrico Zio, Zhonghai Ma

ABSTRACT

With the development of debris detection techniques, wear debris has become a powerful indicator for wear conditions monitoring of engineering machines. However, there is still a lack of effective method for predicting the generation of wear debris with given rough surfaces. Hence, a numerical model is developed based on atomic attrition mechanism. Boundary element method is used to solve the dry sliding contact problem. A discretized solution is used to calculate subsurface stress. From the quantity, size, and shape perspectives, wear debris is analyzed using the detailed information by a Monte Carlo simulation on 100 pairs of rough surfaces. The predictions are compared with results by the existing models quantitatively or qualitatively. More... »

PAGES

38

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11249-019-1150-2

DOI

http://dx.doi.org/10.1007/s11249-019-1150-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112388443


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s11249-019-1150-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s11249-019-1150-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11249-019-1150-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11249-019-1150-2'


 

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