Using a break prediction model for drinking water networks asset management: From research to practice - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Access content directly
Journal Articles Water Science and Technology: Water Supply Year : 2012

Using a break prediction model for drinking water networks asset management: From research to practice

L’utilisation d’un modèle de prédiction des cases pour la gestion patrimoniale des réseaux de distribution d’eau potable : De la recherché à la pratique

Eddy Renaud
Yves Le Gat
M. Poulton
  • Function : Author

Abstract

Break prediction models can help water utility decision-makers to build pipe rehabilitation programs. For many years, using them has been a specialist matter. After more than 15 years of research into the ageing of water pipes, Irstea (formerly Cemagref) has developed the Linear Extension of the Yule Process (LEYP) model based on counting process theory, which relies not only on a pipe’s characteristics and environment but also on its age and previous breaks. It was then decided to develop a break prediction tool usable by water utilities: the ‘Casses’ freeware. To make this possible, it was necessary to deal with several constraints. To cope with the diversity of available data for various water utilities, flexible input data formats were designed as well as an importation module which checks the conformity and coherence of data. Tools for data management and an advice module dedicated to model calibration were conceived for non-statistician users. The break prediction results can be used directly to compare break evolution with different rehabilitation strategies and they can also feed multicriteria decision tools. In this case, the ‘Casses’ freeware can work as a ‘slave’ of the integrated application.
No file

Dates and versions

hal-02597881 , version 1 (15-05-2020)

Identifiers

Cite

Eddy Renaud, Yves Le Gat, M. Poulton. Using a break prediction model for drinking water networks asset management: From research to practice. Water Science and Technology: Water Supply, 2012, 12 (5), pp.674-682. ⟨hal-02597881⟩

Collections

IRSTEA INRAE
19 View
0 Download

Share

Gmail Mastodon Facebook X LinkedIn More