Department Urban Water Management

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      originalId => protected6700 (integer)
      authors => protected'Scheidegger, A.; Hug, T.; Rieckermann, J.; Maurer, M.' (73 chars)
      title => protected'Network condition simulator for benchmarking sewer deterioration models' (71 chars)
      journal => protected'Water Research' (14 chars)
      year => protected2011 (integer)
      volume => protected45 (integer)
      issue => protected'16' (2 chars)
      startpage => protected'4983' (4 chars)
      otherpage => protected'4994' (4 chars)
      categories => protected'sewerage; deterioration model; semi-Markov chain; asset management; pipe con
         dition inspection' (93 chars)
      description => protected'Anaccurate description of aging and deterioration of urban drainage systemsi
         s necessary for optimal investment and rehabilitation planning. Due to a gen
         eral lack of suitable datasets, network condition models are rarely validate
         d, and if so with varying levels of success. We therefore propose a novel ne
         twork condition simulator (NetCoS) that produces a synthetic population of s
         ewer sections with a given condition-class distribution. NetCoS can be used 
         to benchmark deterioration models and guide utilities in the selection of ap
         propriate models and data management strategies. The underlying probabilisti
         c model considers three main processes: a) deterioration, b) replacement pol
         icy, and c) expansions of the sewer network. The deterioration model feature
         s a semi-Markov chain that uses transition probabilities based on user-defin
         ed survival functions. The replacement policy is approximated with a conditi
         on-class dependent probability of replacing a sewer pipe. The model then sim
         ulates the course of the sewer sections from the installation of the first l
         ine to the present, adding new pipes based on the defined replacement and ex
         pansion program. We demonstrate the usefulness of NetCoS in two examples whe
         re we quantify the influence of incomplete data and inspection frequency on 
         the parameter estimation of a cohort survival model and a Markov deteriorati
         on model. Our results show that typical available sewer inventory data with 
         discarded historical data overestimate the average life expectancy by up to 
         200 years. Although NetCoS cannot prove the validity of a particular deterio
         ration model, it is useful to reveal its possible limitations and shortcomin
         gs and quantifies the effects of missing or uncertain data. Future developme
         nts should include additional processes, for example to investigate the long
         -term effect of pipe rehabilitation measures, such as inliners.' (1887 chars)
      serialnumber => protected'0043-1354' (9 chars)
      doi => protected'10.1016/j.watres.2011.07.008' (28 chars)
      uid => protected6700 (integer)
      _localizedUid => protected6700 (integer)modified
      _languageUid => protectedNULL
      _versionedUid => protected6700 (integer)modified
      pid => protected124 (integer)