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Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces

The roughness of material surfaces is of greatest relevance for applications. These include wear, friction, fatigue, cytocompatibility, or corrosion resistance. Today’s descriptors of the International Organization for Standardization show varying performance in discriminating surface roughness patt...

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Autores principales: Senge, Jan F., Astaraee, Asghar Heydari, Dłotko, Pawel, Bagherifard, Sara, Bosbach, Wolfram A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976008/
https://www.ncbi.nlm.nih.gov/pubmed/35365741
http://dx.doi.org/10.1038/s41598-022-09551-9
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author Senge, Jan F.
Astaraee, Asghar Heydari
Dłotko, Pawel
Bagherifard, Sara
Bosbach, Wolfram A.
author_facet Senge, Jan F.
Astaraee, Asghar Heydari
Dłotko, Pawel
Bagherifard, Sara
Bosbach, Wolfram A.
author_sort Senge, Jan F.
collection PubMed
description The roughness of material surfaces is of greatest relevance for applications. These include wear, friction, fatigue, cytocompatibility, or corrosion resistance. Today’s descriptors of the International Organization for Standardization show varying performance in discriminating surface roughness patterns. We introduce here a set of surface parameters which are extracted from the appropriate persistence diagram with enhanced discrimination power. Using the finite element method implemented in Abaqus Explicit 2019, we modelled American Rolling Mill Company pure iron specimens (volume 1.5 × 1.5 × 1.0 mm(3)) exposed to a shot peening procedure. Surface roughness evaluation after each shot impact and single indents were controlled numerically. Conventional and persistence-based evaluation is implemented in Python code and available as open access supplement. Topological techniques prove helpful in the comparison of different shot peened surface samples. Conventional surface area roughness parameters might struggle in distinguishing different shot peening surface topographies, in particular for coverage values > 69%. Above that range, the calculation of conventional parameters leads to overlapping descriptor values. In contrast, lifetime entropy of persistence diagrams and Betti curves provide novel, discriminative one-dimensional descriptors at all coverage ranges. We compare how conventional parameters and persistence parameters describe surface roughness. Conventional parameters are outperformed. These results highlight how topological techniques might be a promising extension of surface roughness methods.
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spelling pubmed-89760082022-04-05 Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces Senge, Jan F. Astaraee, Asghar Heydari Dłotko, Pawel Bagherifard, Sara Bosbach, Wolfram A. Sci Rep Article The roughness of material surfaces is of greatest relevance for applications. These include wear, friction, fatigue, cytocompatibility, or corrosion resistance. Today’s descriptors of the International Organization for Standardization show varying performance in discriminating surface roughness patterns. We introduce here a set of surface parameters which are extracted from the appropriate persistence diagram with enhanced discrimination power. Using the finite element method implemented in Abaqus Explicit 2019, we modelled American Rolling Mill Company pure iron specimens (volume 1.5 × 1.5 × 1.0 mm(3)) exposed to a shot peening procedure. Surface roughness evaluation after each shot impact and single indents were controlled numerically. Conventional and persistence-based evaluation is implemented in Python code and available as open access supplement. Topological techniques prove helpful in the comparison of different shot peened surface samples. Conventional surface area roughness parameters might struggle in distinguishing different shot peening surface topographies, in particular for coverage values > 69%. Above that range, the calculation of conventional parameters leads to overlapping descriptor values. In contrast, lifetime entropy of persistence diagrams and Betti curves provide novel, discriminative one-dimensional descriptors at all coverage ranges. We compare how conventional parameters and persistence parameters describe surface roughness. Conventional parameters are outperformed. These results highlight how topological techniques might be a promising extension of surface roughness methods. Nature Publishing Group UK 2022-04-01 /pmc/articles/PMC8976008/ /pubmed/35365741 http://dx.doi.org/10.1038/s41598-022-09551-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Senge, Jan F.
Astaraee, Asghar Heydari
Dłotko, Pawel
Bagherifard, Sara
Bosbach, Wolfram A.
Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title_full Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title_fullStr Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title_full_unstemmed Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title_short Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
title_sort extending conventional surface roughness iso parameters using topological data analysis for shot peened surfaces
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976008/
https://www.ncbi.nlm.nih.gov/pubmed/35365741
http://dx.doi.org/10.1038/s41598-022-09551-9
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