Physical characteristics of pipes as indicators of structural state for decision-making considerations in sewer asset management

Sewer deterioration is a problem that affects many cities of the world. This affects the structural state of the sewer systems, as well as its hydraulic capacity and the service level. As a consequence, the sewer system stakeholders are working on the development of a proactive sewer management to m...

Full description

Autores:
López-Kleine, Liliana
Hernandez, Nathalie
Torres, Andres
Tipo de recurso:
Article of journal
Fecha de publicación:
2016
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/67609
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/67609
http://bdigital.unal.edu.co/68638/
Palabra clave:
62 Ingeniería y operaciones afines / Engineering
k-means
sewer asset management
cluster analysis
Principal Components Analysis (PCA)
proactive sewer management
sewer pipes
structural pipes state
Bogota’s sewer system
k-means
gestión de sistemas de alcantarillado
cluster
análisis de componentes principales (ACP)
gestión proactiva de alcantarillados
tuberías de alcantarillado
condición estructural de tuberías de alcantarillado
sistema de alcantarillado de Bogotá
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Sewer deterioration is a problem that affects many cities of the world. This affects the structural state of the sewer systems, as well as its hydraulic capacity and the service level. As a consequence, the sewer system stakeholders are working on the development of a proactive sewer management to make decision in time and avoid public emergencies. Therefore, the objective of this work was to predict the variable state using a clustering algorithm (k-means) in Bogotá’s sewer pipes based on its physical characteristics. Among the most representative results was to find a relationship between pipes’ characteristics and their structural state (chi-squared). Furthermore, the slope and ground level variables were the most related ones to the state of the pipes. The detected relationships are linear and can be used to make management decisions when pipes are clustered and the clusters are mapped on a principal component plane.