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Venelles, France

Ahmadi M.,G2C Environnement | Cherqui F.,University of Lyon | Cherqui F.,University Claude Bernard Lyon 1 | Aubin J.-B.,INSA Lyon | And 3 more authors.
Urban Water Journal | Year: 2016

Utilities are faced with the challenge of how to manage their assets cost-effectively while providing safe and reliable services to their customers (Marlow et al., 2007). A small number of utilities have completely inspected their sewer networks. Therefore, the use of an asset stock's sample to calibrate deterioration models and to study scenarios about the future seems mandatory. This sample should reflect the asset stock's characteristics in the best manner. However, authors have calibrated deterioration models without paying attention to the impact of used samples on their outcomes. The main scopes of this article are then to: 1) draw a representative sample of an asset stock, 2) provide a reliable estimation of a specific property of the asset stock from this sample and 3) study the impact of calibration sample on the outcomes of a multivariate model. We show that the calibration of deterioration models depends heavily on the characteristics of the used sample. © 2015 Taylor & Francis. Source

Ahmadi M.,INSA Lyon | Cherqui F.,University Claude Bernard Lyon 1 | Cherqui F.,University of Lyon | De Massiac J.-C.,G2C Environnement | And 2 more authors.
European Journal of Environmental and Civil Engineering | Year: 2014

The purpose of this paper is to discuss the influence of data availability and quality within a utility to prioritise inspection and rehabilitation needs. Data are required in order to predict the structural condition of assets. Lack of data and budget limitation do not encourage utilities to evolve from reactive to proactive management. Methods and tools exist; however, improving operational practices will require the demonstration of data collection benefits. In this article, asset management approaches are presented and discussed regarding influence of data; from closed-circuit television reports elaboration to prioritisation of rehabilitation needs. Bottlenecks related to uncertainty, imprecision and incompleteness of data are identified, and the authors propose approaches to study these questions. This article also highlights the use of numerical experiment to simulate asset management scenarios, to experiment methods or to demonstrate the interest of new practices. Numerical experiment allows construction and use of virtual degraded databases derived from a completely known asset stock. © 2014 © 2014 Taylor & Francis. Source

Berthault D.,Ministere de lEcologie | Bulleryal E.,Office National de lEau et des Milieux Aquatiques | Cousin A.-C.,Veolia | Nirsimloo K.,G2C Environnement | Renaud E.,IRSTEA
Techniques - Sciences - Methodes | Year: 2011

Grenelle 2 environmental Act is the continuation of the Grenelle 1 Act that defined the government objectives in the environmental field. Article 161 of Grenelle 2 Act is related to the improvement of water losses levels on drinking water networks. It refers to a "water losses rate" and to an "actions plan"; these are two topics on which Astee is likely to bring a technical contribution. The water losses rate of a water service can be evaluated thanks to performance indicators. However, it is complicated to compare networks on the basis of these performance indicators since they are not taking into account all the parameters that influence water losses (such as connection density, water pressure, conditions of the network and its environment). Nowadays, the main actions to tackle water losses are well known. However, their efficiency depends on the network characteristics (and the actions already carried out). There is no universal solution adaptable to all networks. It is thus necessary to study the network assets and their operation in order to set up relevant and adapted solutions. The work done by the Astee group is not terminated. This document presents its progresses. Source

Ahmadi M.,G2C Environnement | Ahmadi M.,INSA Lyon | Cherqui F.,University of Lyon | Cherqui F.,University Claude Bernard Lyon 1 | And 5 more authors.
Structure and Infrastructure Engineering | Year: 2014

Asset management is an increasing concern for the water and wastewater industry. Condition assessment of sewer segments is an important component of sewer asset management and relies mostly on visual inspection. Observed defects are translated into a score for each segment. Although most protocols give a segment a condition grade by comparing its score with a subjective scale of numerical values, we propose a protocol to calibrate thresholds for each asset stock. Thresholds are calculated according to two sets of parameters: overall condition of the asset stock in question (estimated by a representative sample or provided by the utility manager) and assignment-error weighting (determined by the utility manager) linked to either over-estimation or under-estimation of condition grade. This method is applied to 150 km of sewers from the Greater Lyon asset stock. Sensitivity analyses of these parameters are then implemented. Three hypotheses about overall condition of the asset stock are combined with three matrices of assignment-error weights. Both parameters influence thresholds and change the assessment of the studied segments. The synthesis of such sensitivity analyses can be used to prioritise complementary investigations. © 2013 Taylor & Francis. Source

Ahmadi M.,G2C Environnement | Ahmadi M.,INSA Lyon | Cherqui F.,University of Lyon | Cherqui F.,University Claude Bernard Lyon 1 | And 3 more authors.
Urban Water Journal | Year: 2014

One key aspect of sewer inspection programs is the prediction of sewer condition. Despite the development of deterioration models, the influence of available data on models' predictive power has not been studied in depth. In this article, numerical experiments on a semi-virtual asset stock have been conducted to answer two main questions: how to establish a list of the most informative factors and whether it is better to have data imprecision instead of data incompleteness in a utility database. Two approaches for establishing a list of the most informative factors are compared. The results show a statistical analysis (a priori analysis) can predict the impact of available data on inspection program efficiency (a posteriori analysis). This can be used to plan data acquisition programs. Finally, we show that using the notion of "district" (data imprecision) can provide efficient results when the most informative factor "age" is not available (data incompleteness). © 2013 © 2013 Taylor & Francis. Source

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