TY - JOUR
T1 - Physical characteristics of pipes as indicators of structural state for decision-making considerations in sewer asset management
AU - López-Kleine, Liliana
AU - Hernández, Nathalie
AU - Torres, Andrés
N1 - Publisher Copyright:
© 2016, Revista Ingenieria e Investigacion - Editorial Board. All rights reserved.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Bogota’s sewer system
KW - Cluster analysis
KW - K-means
KW - Principal components analysis (PCA)
KW - Proactive sewer mana-gement
KW - Sewer asset management
KW - Sewer pipes
KW - Structural pipes state
UR - http://www.scopus.com/inward/record.url?scp=85006788830&partnerID=8YFLogxK
U2 - 10.15446/ing.investig.v36n3.56616
DO - 10.15446/ing.investig.v36n3.56616
M3 - Article
AN - SCOPUS:85006788830
SN - 0120-5609
VL - 36
SP - 15
EP - 21
JO - Ingenieria e Investigacion
JF - Ingenieria e Investigacion
IS - 3
ER -