Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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Kücükyildiz, Ömer Can

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Technical University of Denmark

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (9/9 displayed)

  • 2022Rapid Screening of the Mechanical Properties of 13 wt%Cr Steels with Uncharted Combinations of C and N Contents2citations
  • 2022Area determination with pile-up and sink-in in nanoindentation of oxygen containing titanium22citations
  • 2021Extreme hardening of titanium with colossal interstitial contents of nitrogen and oxygen20citations
  • 2020Anisotropy effects on gaseous nitriding of austenitic stainless steel single crystals29citations
  • 2020Thermo-chemical-mechanical simulation of low temperature nitriding of austenitic stainless steel; inverse modelling of surface reaction rates18citations
  • 2018Residual stress in expanded austenite on stainless steel; origin, measurement, and prediction22citations
  • 2018Numerical Modelling of Mechanical Anisotropy during Low Temperature Nitriding of Stainless Steelcitations
  • 2018A simple model linking surface roughness with friction coefficient and manufacturing costcitations
  • 2017Integrated Computational Modelling of Thermochemical Surface Engineering of Stainless Steelcitations

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Chart of shared publication
Somers, Marcel Adrianius Johannes
8 / 195 shared
Villa, Matteo
1 / 52 shared
Dahl, Kristian Vinter
1 / 60 shared
Poulios, Konstantinos
1 / 21 shared
Mahdavi, H.
1 / 3 shared
Kværndrup, Frederik B.
2 / 7 shared
Engelbrekt, Christian
1 / 8 shared
Winther, Grethe
5 / 55 shared
Grumsen, Flemming Bjerg
1 / 33 shared
Hattel, Jh
4 / 160 shared
Thorborg, Jesper
3 / 26 shared
Sonne, Mads S.
3 / 19 shared
Ormstrup, Casper A.
1 / 2 shared
Alimadadi, Hossein
1 / 22 shared
Chiffre, Leonardo De
1 / 39 shared
Bay, Niels Oluf
1 / 41 shared
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Co-Authors (by relevance)

  • Somers, Marcel Adrianius Johannes
  • Villa, Matteo
  • Dahl, Kristian Vinter
  • Poulios, Konstantinos
  • Mahdavi, H.
  • Kværndrup, Frederik B.
  • Engelbrekt, Christian
  • Winther, Grethe
  • Grumsen, Flemming Bjerg
  • Hattel, Jh
  • Thorborg, Jesper
  • Sonne, Mads S.
  • Ormstrup, Casper A.
  • Alimadadi, Hossein
  • Chiffre, Leonardo De
  • Bay, Niels Oluf
OrganizationsLocationPeople

article

A simple model linking surface roughness with friction coefficient and manufacturing cost

  • Chiffre, Leonardo De
  • Bay, Niels Oluf
  • Kücükyildiz, Ömer Can
Abstract

<p>A simple theoretical model linking surface micro geometry, friction and manufacturing cost is presented. Combining a basic geometrical relationship of plastic deformation of workpiece surface asperities by a hard tool with an assumption of adhesive friction, the friction coefficient of a soft, rough surface sliding against a hard, smooth tool surface can be calculated, linking surface roughness with friction coefficient. The simple model can also link the cost related to manufacturing with a surface characterized by a given friction coefficient value. Results are presented from tests carried out to verify the simple model. Several test pieces were manufactured by turning, or grooving, an aluminum alloy and brass using different feeds, tool nose radii, and tool nose angles, achieving different surface profiles. The surfaces were characterized using a stylus profilometer and a digital microscope. The static friction coefficient was determined in terms of angle of repose using a rotary table. The experimentally determined values of the friction coefficient were compared with those predicted from feed, tool radius, and asperity angle. The tests have shown a good reproducibility, and a clear determination of the friction coefficient was possible. However, due to the low normal loads involved in this set up, the influence from the surface roughness was not clear. Further investigations are therefore proposed.</p>

Topics
  • impedance spectroscopy
  • surface
  • polymer
  • aluminium
  • brass