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Multiscale characterizations of surface anisotropies
Poznan University of Technology, Poland.
RISE Research Institutes of Sweden, Material och produktion, Tillverkningsprocesser. Chalmers University of Technology, Sweden.ORCID-id: 0000-0003-3656-1806
Worcester Polytechnic Institute, USA.
2020 (engelsk)Inngår i: Materials, E-ISSN 1996-1944, Vol. 13, nr 13, artikkel-id 3028Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Anisotropy can influence surface function and can be an indication of processing. These influences and indications include friction, wetting, and microwear. This article studies two methods for multiscale quantification and visualization of anisotropy. One uses multiscale curvature tensor analysis and shows anisotropy in horizontal coordinates i.e., topocentric. The other uses multiple bandpass filters (also known as sliding bandpass filters) applied prior to calculating anisotropy parameters, texture aspect ratios (Str) and texture directions (Std), showing anisotropy in horizontal directions only. Topographies were studied on two milled steel surfaces, one convex with an evident large scale, cylindrical form anisotropy, the other nominally flat with smaller scale anisotropies; a EDMed surface, an example of an isotropic surface; and an additively manufactured surface with pillar-like features. Curvature tensors contain the two principal curvatures, i.e., maximum and minimum curvatures, which are orthogonal, and their directions, at each location. Principal directions are plotted for each calculated location on each surface, at each scale considered. Histograms in horizontal coordinates show altitude and azimuth angles of principal curvatures, elucidating dominant texture directions at each scale. Str and Std do not show vertical components, i.e., altitudes, of anisotropy. Changes of anisotropy with scale categorically failed to be detected by traditional characterization methods used conventionally. These multiscale methods show clearly in several representations that anisotropy changes with scale on actual surface measurements with markedly different anisotropies.

sted, utgiver, år, opplag, sider
MDPI AG , 2020. Vol. 13, nr 13, artikkel-id 3028
Emneord [en]
Anisotropy, Multiscale, Surface texture, Aspect ratio, Bandpass filters, Surface measurement, Tensors, Textures, Wetting, Anisotropy parameters, Characterization methods, Horizontal coordinates, Multi-scale curvatures, Multiscale characterizations, Principal curvature, Principal directions, Vertical component
HSV kategori
Identifikatorer
URN: urn:nbn:se:ri:diva-45617DOI: 10.3390/ma13133028Scopus ID: 2-s2.0-85088035379OAI: oai:DiVA.org:ri-45617DiVA, id: diva2:1458065
Merknad

Funding details: 0614/SBAD/1529; Funding text 1: This research was funded by the Polish Ministry of Science and Higher, as a part of research subsidy 0614/SBAD/1529. The authors would like to acknowledge previous contributions of Matthew Gleason, a student at WPI, who developed an algorithm for multiscale curvature analysis that led to several papers and discovering a strong correlation with curvature, and of Torbjorn S. Bergstron, who, as a grad student at WPI, developed the first multiscale anisotropy analyses, that are now widely used in physical anthropology.

Tilgjengelig fra: 2020-08-13 Laget: 2020-08-13 Sist oppdatert: 2024-07-04bibliografisk kontrollert

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