Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota

The aim of this work is to identify and quantify physical and environmental explanatory variables for the structural state of urban drainage networks in a pilot study located in Bogota, Colombia. The analysis used information from 2291 CCTV inspections collected by the Water and Sewerage Company of...

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Autores:
Angarita, H
Niño, P
Vargas, D
Hernández, N
Torres, A
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/67571
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/67571
http://bdigital.unal.edu.co/68600/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
CCTV
explanatory variables
sewer asset management
sewer system
structural failure
CCTV
gestión patrimonial
factores de riesgo
fallos estructurales
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
id UNACIONAL2_e2fdb7e678d4a940ca408db70dd5ee7d
oai_identifier_str oai:repositorio.unal.edu.co:unal/67571
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
title Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
spellingShingle Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
62 Ingeniería y operaciones afines / Engineering
CCTV
explanatory variables
sewer asset management
sewer system
structural failure
CCTV
gestión patrimonial
factores de riesgo
fallos estructurales
title_short Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
title_full Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
title_fullStr Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
title_full_unstemmed Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
title_sort Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota
dc.creator.fl_str_mv Angarita, H
Niño, P
Vargas, D
Hernández, N
Torres, A
dc.contributor.author.spa.fl_str_mv Angarita, H
Niño, P
Vargas, D
Hernández, N
Torres, A
dc.subject.ddc.spa.fl_str_mv 62 Ingeniería y operaciones afines / Engineering
topic 62 Ingeniería y operaciones afines / Engineering
CCTV
explanatory variables
sewer asset management
sewer system
structural failure
CCTV
gestión patrimonial
factores de riesgo
fallos estructurales
dc.subject.proposal.spa.fl_str_mv CCTV
explanatory variables
sewer asset management
sewer system
structural failure
CCTV
gestión patrimonial
factores de riesgo
fallos estructurales
description The aim of this work is to identify and quantify physical and environmental explanatory variables for the structural state of urban drainage networks in a pilot study located in Bogota, Colombia. The analysis used information from 2291 CCTV inspections collected by the Water and Sewerage Company of Bogota (EAAB, from its Spanish initials) using tele-operated equipment during 2008-2010. Linear regression models were established to identify the environmental and physical characteristics of the pipes that are significantly associated with the occurrence, magnitude and type of the failures commonly found. Despite the fact that the correlation levels show that the developed model has a very low predictive capacity, it was found that the process of selecting assets for CCTV inspection can be optimized, increasing the success rate in failure detection.
publishDate 2017
dc.date.issued.spa.fl_str_mv 2017-05-01
dc.date.accessioned.spa.fl_str_mv 2019-07-03T04:34:22Z
dc.date.available.spa.fl_str_mv 2019-07-03T04:34:22Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.issn.spa.fl_str_mv ISSN: 2248-8723
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/67571
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identifier_str_mv ISSN: 2248-8723
url https://repositorio.unal.edu.co/handle/unal/67571
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dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.spa.fl_str_mv https://revistas.unal.edu.co/index.php/ingeinv/article/view/57752
dc.relation.ispartof.spa.fl_str_mv Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e Investigación
Ingeniería e Investigación
dc.relation.references.spa.fl_str_mv Angarita, H and Niño, P and Vargas, D and Hernández, N and Torres, A (2017) Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota. Ingeniería e Investigación, 37 (2). pp. 6-16. ISSN 2248-8723
dc.rights.spa.fl_str_mv Derechos reservados - Universidad Nacional de Colombia
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial 4.0 Internacional
Derechos reservados - Universidad Nacional de Colombia
http://creativecommons.org/licenses/by-nc/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ingeniería
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/67571/1/57752-344256-1-PB.pdf
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spelling Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Angarita, H7bf9f58a-a6d5-4594-996e-58fc10bfd227300Niño, P719ed523-4757-4bab-98b4-095b41f20436300Vargas, Db0580f16-3744-49ad-b6c8-039e30e5a8c8300Hernández, N405d9109-500c-402b-8473-f13e408fa3a7300Torres, A822fa7a3-5427-444f-b159-7df0c8da5f6a3002019-07-03T04:34:22Z2019-07-03T04:34:22Z2017-05-01ISSN: 2248-8723https://repositorio.unal.edu.co/handle/unal/67571http://bdigital.unal.edu.co/68600/The aim of this work is to identify and quantify physical and environmental explanatory variables for the structural state of urban drainage networks in a pilot study located in Bogota, Colombia. The analysis used information from 2291 CCTV inspections collected by the Water and Sewerage Company of Bogota (EAAB, from its Spanish initials) using tele-operated equipment during 2008-2010. Linear regression models were established to identify the environmental and physical characteristics of the pipes that are significantly associated with the occurrence, magnitude and type of the failures commonly found. Despite the fact that the correlation levels show that the developed model has a very low predictive capacity, it was found that the process of selecting assets for CCTV inspection can be optimized, increasing the success rate in failure detection.Este artículo presenta los resultados de un estudio piloto realizado en la ciudad de Bogotá para identificar y cuantificar factores de riesgo físicos y/o ambientales de las redes de drenaje urbano, en el marco de un enfoque proactivo de gestión patrimonial de la infraestructura de servicios públicos. El análisis utiliza información de 2291 inspecciones de CCTV recopiladas por la Empresa de Acueducto y Alcantarillado de Bogotá (EAAB) mediante equipos tele-operados durante los años 2008 a 2010. Mediante modelos de regresión lineal se establecieron entre el conjunto de variables recopiladas mediante procesos de inspección por CCTV, aquellas que muestran una asociación estadísticamente significativa con la ocurrencia, magnitud y/o tipo de fallos que típicamente se encuentran en las conducciones, entre otras, material (Gres y P.V.C) y diámetro de la tubería. Los resultados muestran que es posible optimizar los recursos para la inspección de las redes con fines de mejorar la tasa de éxito en la detección de fallos.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ingenieríahttps://revistas.unal.edu.co/index.php/ingeinv/article/view/57752Universidad Nacional de Colombia Revistas electrónicas UN Ingeniería e InvestigaciónIngeniería e InvestigaciónAngarita, H and Niño, P and Vargas, D and Hernández, N and Torres, A (2017) Identifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of Bogota. Ingeniería e Investigación, 37 (2). pp. 6-16. ISSN 2248-872362 Ingeniería y operaciones afines / EngineeringCCTVexplanatory variablessewer asset managementsewer systemstructural failureCCTVgestión patrimonialfactores de riesgofallos estructuralesIdentifying explanatory variables of structural state for optimum asset management of urban drainage networks: a pilot study for the city of BogotaArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL57752-344256-1-PB.pdfapplication/pdf1199464https://repositorio.unal.edu.co/bitstream/unal/67571/1/57752-344256-1-PB.pdf11c134a0d4e2e3609ed1bd4000919b3dMD51THUMBNAIL57752-344256-1-PB.pdf.jpg57752-344256-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg8501https://repositorio.unal.edu.co/bitstream/unal/67571/2/57752-344256-1-PB.pdf.jpgbbcaf6a73a999edc304accfd4c7346f0MD52unal/67571oai:repositorio.unal.edu.co:unal/675712024-05-22 23:33:47.154Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co

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