In this section
Many Tribology Group publications are Open Access thanks to funding from the EPSRC.
@inbook{Boidi:2021:10.5772/intechopen.100245,
author = {Boidi, G and Grützmacher, P and Varga, M and da, Silva MR and Gachot, C and Dini, D and Profito, F and Machado, I},
booktitle = {Tribology},
doi = {10.5772/intechopen.100245},
editor = {Pintaude and Cousseau},
title = {Tribological performance of random sinter pores vs. deterministic laser surface textures: an experimental and machine learning approach},
url = {http://dx.doi.org/10.5772/intechopen.100245},
year = {2021}
}
TY - CHAP
AB - This work critically scrutinizes and compares the tribological performance of randomly distributed surface pores in sintered materials and precisely tailored laser textures produced by different laser surface texturing techniques. The pore distributions and dimensions were modified by changing the sintering parameters, while the topological features of the laser textures were varied by changing the laser sources and structuring parameters. Ball-on-disc tribological experiments were carried out under lubricated combined sliding-rolling conditions. Film thickness was measured in-situ through a specific interferometry technique developed for the study of rough surfaces. Furthermore, a machine learning approach based on the radial basis function method was proposed to predict the frictional behavior of contact interfaces with surface irregularities. The main results show that both sintered and laser textured materials can reduce friction compared to the untextured material under certain operating conditions. Moreover, the machine learning model was shown to predict results with satisfactory accuracy. It was also found that the performance of sintered materials could lead to similar improvements as achieved by textured surfaces, even if surface pores are randomly distributed and not precisely controlled.
AU - Boidi,G
AU - Grützmacher,P
AU - Varga,M
AU - da,Silva MR
AU - Gachot,C
AU - Dini,D
AU - Profito,F
AU - Machado,I
DO - 10.5772/intechopen.100245
PY - 2021///
TI - Tribological performance of random sinter pores vs. deterministic laser surface textures: an experimental and machine learning approach
T1 - Tribology
UR - http://dx.doi.org/10.5772/intechopen.100245
UR - https://www.intechopen.com/online-first/78932
UR - http://hdl.handle.net/10044/1/97250
ER -