title: Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing.
abstract: Oslo Vann og Avløpsetaten (Oslo VAV)-the water/wastewater utility in the Norwegian capital city of Oslo-is assessing future strategies for selection of most reliable materials for wastewater networks, taking into account not only material technical performance but also material performance, regarding operational condition of the system.The research project undertaken by SINTEF Group, the largest research organisation in Scandinavia, NTNU (Norges Teknisk-Naturvitenskapelige Universitet) and Oslo VAV adopts several approaches to understand reasons for failures that may impact flow capacity, by analysing historical data for blockages in Oslo.The aim of the study was to understand whether there is a relationship between the performance of the pipeline and a number of specific attributes such as age, material, diameter, to name a few. This paper presents the characteristics of the data set available and discusses the results obtained by performing two different approaches: a traditional statistical analysis by segregating the pipes into classes, each of which with the same explanatory variables, and a Evolutionary Polynomial Regression model (EPR), developed by Technical University of Bari and University of Exeter, to identify possible influence of pipe's attributes on the total amount of predicted blockages in a period of time.Starting from a detailed analysis of the available data for the blockage events, the most important variables are identified and a classification scheme is adopted.From the statistical analysis, it can be stated that age, size and function do seem to have a marked influence on the proneness of a pipeline to blockages, but, for the reduced sample available, it is difficult to say which variable it is more influencing. If we look at total number of blockages the oldest class seems to be the most prone to blockages, but looking at blockage rates (number of blockages per km per year), then it is the youngest class showing the highest blockage rate. EPR allowed identifying the relation between attitude to block and pipe's attributes in order to understand what affects the possibility to have a blockage in the pipe. EPR provides formulae to compute the accumulated number of blockages for a pipe class at the end of a given period of time. Those formulae do not represent simply regression models but highlight those variables which affect the physical phenomenon in question.
authors.affiliation: DISTART, Bologna University, Bologna 40126, Italy. rita.ugarelli@mail.ing.unibo.it
authors.forename: Rita
authors.initials: R
authors.lastname: Ugarelli
authors.forename: Stig Morten
authors.initials: SM
authors.lastname: Kristensen
authors.forename: Jon
authors.initials: J
authors.lastname: Røstum
authors.forename: Sveinung
authors.initials: S
authors.lastname: Saegrov
authors.forename: Vittorio
authors.initials: V
authors.lastname: Di Federico
mesh_terms: D000465:Algorithms; D002947:Cities; D004323:Drainage, Sanitary / Q000379:methods*; D008422:Materials Testing; D009664:Norway; D018505:Waste Management / Q000295:instrumentation*; D014872:Water Movements