Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments

Detalhes bibliográficos
Autor(a) principal: Scalon, João Domingos
Data de Publicação: 2022
Outros Autores: Silva, Victor Ferreira da, Oliveira, Wélson Antônio de, Peixoto, Mateus Santos
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/56379
Resumo: Aluminium is extensively used in many manufacturing processes because of its intrinsic properties like soft, ductile, high electrical conductivity and highly corrosion resistant. Unfortunately, pure aluminium cannot give a required tensile strength, whereas by adding some other materials like particles of silicon carbide can give a proper strength and converted into a composite with adequate properties which is most suitable in the manufacturing of some specific biomedical instruments. It is well known that size and spatial distributions of particles are both influential in determining the mechanical properties of composite materials and, therefore, statistical characterization of these distributions is of prime importance if we wish to control the quality of the manufacturing processes for these materials. Many researchers have considered quantitative analysis of these features separately, but here we investigate the relationship between size and spatial distribution of the particles over an aluminium matrix. We have considered the actual sizes simply as ‘large’ or ‘small’ and, consequently, the characterization of the particle distribution patterns in the aluminium matrix can be carried out using statistical methods based on the theory of bivariate spatial point processes. We have applied this statistical approach to a sample of an aluminium alloy reinforced with silicon carbide particles. It is shown that the methods provide a complete characterization on the spatial interaction between small and large silicon carbide particles and it can be successfully used in a quality control step for the production of particulate composite materials used in the manufacturing of biomedical instruments.
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spelling Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instrumentsAl-SiCMarked point processesMonte Carlo simulationGibbs modelAluminium alloy with silicon carbideAluminium is extensively used in many manufacturing processes because of its intrinsic properties like soft, ductile, high electrical conductivity and highly corrosion resistant. Unfortunately, pure aluminium cannot give a required tensile strength, whereas by adding some other materials like particles of silicon carbide can give a proper strength and converted into a composite with adequate properties which is most suitable in the manufacturing of some specific biomedical instruments. It is well known that size and spatial distributions of particles are both influential in determining the mechanical properties of composite materials and, therefore, statistical characterization of these distributions is of prime importance if we wish to control the quality of the manufacturing processes for these materials. Many researchers have considered quantitative analysis of these features separately, but here we investigate the relationship between size and spatial distribution of the particles over an aluminium matrix. We have considered the actual sizes simply as ‘large’ or ‘small’ and, consequently, the characterization of the particle distribution patterns in the aluminium matrix can be carried out using statistical methods based on the theory of bivariate spatial point processes. We have applied this statistical approach to a sample of an aluminium alloy reinforced with silicon carbide particles. It is shown that the methods provide a complete characterization on the spatial interaction between small and large silicon carbide particles and it can be successfully used in a quality control step for the production of particulate composite materials used in the manufacturing of biomedical instruments.Universidade Federal de Lavras (UFLA), Departamento de Estatística (DES)2023-03-28T18:48:15Z2023-03-28T18:48:15Z2022-12-31info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfSCALON, J. D. et al. Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments. Brazilian Journal of Biometrics, [S.l.], v. 40, n. 4, p. 428-441, 2022. DOI: 10.28951/bjb.v40i4.614.http://repositorio.ufla.br/jspui/handle/1/56379Brazilian Journal of Biometrics (BJB)reponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessScalon, João DomingosSilva, Victor Ferreira daOliveira, Wélson Antônio dePeixoto, Mateus Santoseng2023-05-26T19:37:54Zoai:localhost:1/56379Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2023-05-26T19:37:54Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
title Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
spellingShingle Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
Scalon, João Domingos
Al-SiC
Marked point processes
Monte Carlo simulation
Gibbs model
Aluminium alloy with silicon carbide
title_short Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
title_full Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
title_fullStr Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
title_full_unstemmed Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
title_sort Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments
author Scalon, João Domingos
author_facet Scalon, João Domingos
Silva, Victor Ferreira da
Oliveira, Wélson Antônio de
Peixoto, Mateus Santos
author_role author
author2 Silva, Victor Ferreira da
Oliveira, Wélson Antônio de
Peixoto, Mateus Santos
author2_role author
author
author
dc.contributor.author.fl_str_mv Scalon, João Domingos
Silva, Victor Ferreira da
Oliveira, Wélson Antônio de
Peixoto, Mateus Santos
dc.subject.por.fl_str_mv Al-SiC
Marked point processes
Monte Carlo simulation
Gibbs model
Aluminium alloy with silicon carbide
topic Al-SiC
Marked point processes
Monte Carlo simulation
Gibbs model
Aluminium alloy with silicon carbide
description Aluminium is extensively used in many manufacturing processes because of its intrinsic properties like soft, ductile, high electrical conductivity and highly corrosion resistant. Unfortunately, pure aluminium cannot give a required tensile strength, whereas by adding some other materials like particles of silicon carbide can give a proper strength and converted into a composite with adequate properties which is most suitable in the manufacturing of some specific biomedical instruments. It is well known that size and spatial distributions of particles are both influential in determining the mechanical properties of composite materials and, therefore, statistical characterization of these distributions is of prime importance if we wish to control the quality of the manufacturing processes for these materials. Many researchers have considered quantitative analysis of these features separately, but here we investigate the relationship between size and spatial distribution of the particles over an aluminium matrix. We have considered the actual sizes simply as ‘large’ or ‘small’ and, consequently, the characterization of the particle distribution patterns in the aluminium matrix can be carried out using statistical methods based on the theory of bivariate spatial point processes. We have applied this statistical approach to a sample of an aluminium alloy reinforced with silicon carbide particles. It is shown that the methods provide a complete characterization on the spatial interaction between small and large silicon carbide particles and it can be successfully used in a quality control step for the production of particulate composite materials used in the manufacturing of biomedical instruments.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-31
2023-03-28T18:48:15Z
2023-03-28T18:48:15Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv SCALON, J. D. et al. Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments. Brazilian Journal of Biometrics, [S.l.], v. 40, n. 4, p. 428-441, 2022. DOI: 10.28951/bjb.v40i4.614.
http://repositorio.ufla.br/jspui/handle/1/56379
identifier_str_mv SCALON, J. D. et al. Statistical characterization of spatial and size distributions of particles in composite materials used in the manufacturing of biomedical instruments. Brazilian Journal of Biometrics, [S.l.], v. 40, n. 4, p. 428-441, 2022. DOI: 10.28951/bjb.v40i4.614.
url http://repositorio.ufla.br/jspui/handle/1/56379
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA), Departamento de Estatística (DES)
publisher.none.fl_str_mv Universidade Federal de Lavras (UFLA), Departamento de Estatística (DES)
dc.source.none.fl_str_mv Brazilian Journal of Biometrics (BJB)
reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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