In recent years, pipe network as well as failure and condition data have changed significantly in Vienna. This is a result of the focused and intensive renewal programs and the use of new methods in leak detection (e.g. noise logger) and condition recording (e.g. condition survey ductile iron pipes). In addition, the maintenance database and its link to the GIS provide efficient options for evaluating failure and pipe and other assets condition data. The so far used failure and condition prediction models of PiReM - software should therefore be revised and new methods such as machine learning should be used. The coordinated renewal of urban infrastructure is becoming more important due to the enormously increasing construction costs and should therefore be taken into account as well, when renewal priorities for drinking water pipes are determined. With the PiReM approach used so far, this was only supported indirectly. In addition to failure prediction models and cost based approaches, in this project expert knowledge, is taken into account for renewal prioritization in form of a multi criteria decision analysis.
|Effective start/end date||15/03/22 → 30/04/23|
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.