Application of deep neural network and gamma-ray scattering in eccentric scale calculation regardless of the fluids volume fraction inside a pipeline.

Gamma Rays Monte Carlo Method Neural Networks, Computer Software
Deep neural network Gamma-ray scattering MCNP6 code Multiphase flow Scale

Journal

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
ISSN: 1872-9800
Titre abrégé: Appl Radiat Isot
Pays: England
ID NLM: 9306253

Informations de publication

Date de publication:
Oct 2022
Historique:
received: 23 02 2022
revised: 24 06 2022
accepted: 26 06 2022
pubmed: 7 7 2022
medline: 2 9 2022
entrez: 6 7 2022
Statut: ppublish

Résumé

Scale formation is one of the major problems in the oil industry as it can accumulate on the surface of the pipelines, which could even fully block the fluids' passage. It was developed a methodology to detect and quantify the maximum thickness of eccentric scale inside pipelines using nuclear techniques and an artificial neural network. The measurement procedure is based on gamma-ray scattering using NaI(Tl) detectors and a

Identifiants

DOI: 10.1016/j.apradiso.2022.110353 PMID: 35792355
pubmed: 35792355
pii: S0969-8043(22)00242-1
doi: 10.1016/j.apradiso.2022.110353
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

110353

Informations de copyright

Copyright © 2022 Elsevier Ltd. All rights reserved.

Auteurs

Roos Sophia de Freitas Dam (RSF)

Universidade Federal Do Rio de Janeiro - UFRJ, Programa de Engenharia Nuclear - PEN/COPPE, Avenida Horácio de Macedo 2030, G - 206, 21941-914, Cidade Universitária, RJ, Brazil; Instituto de Engenharia Nuclear - IEN, Divisão de Radiofármacos - DIRAD, Rua Hélio de Almeida 75, 21941-906, Cidade Universitária, RJ, Brazil. Electronic address: rdam@coppe.ufrj.br.

William Luna Salgado (WL)

Instituto de Engenharia Nuclear - IEN, Divisão de Radiofármacos - DIRAD, Rua Hélio de Almeida 75, 21941-906, Cidade Universitária, RJ, Brazil. Electronic address: william.otero@coppe.ufrj.br.

Roberto Schirru (R)

Universidade Federal Do Rio de Janeiro - UFRJ, Programa de Engenharia Nuclear - PEN/COPPE, Avenida Horácio de Macedo 2030, G - 206, 21941-914, Cidade Universitária, RJ, Brazil. Electronic address: schirru@lmp.ufrj.br.

César Marques Salgado (CM)

Instituto de Engenharia Nuclear - IEN, Divisão de Radiofármacos - DIRAD, Rua Hélio de Almeida 75, 21941-906, Cidade Universitária, RJ, Brazil. Electronic address: otero@ien.gov.br.

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Classifications MeSH

questionsmedicales.fr › Phénomènes physiques › Rayonnement › Rayonnement ionisant › Rayons gamma › Application of deep neural network and...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Statistiques comme sujet › Méthode de Monte Carlo › Application of deep neural network and...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Réseaux neuronaux (ordinateur) › Application of deep neural network and...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Logiciel › Application of deep neural network and...