Risk calculations for transport pipe replacement

EVN Wasser provides drinking water to 637.000 inhabitants. EVN intends to renew the circa 122 km AC transportation pipe network in the Rußbachtal, North of Vienna. This will require a substantial investment. To schedule the investment in the coming years optimally and accountably, a data driven asset management approach was erquested.

Client: EVN Wasser
Country: Austria
Period: 2024

Approach and solution

For many years, Spatial Insight has been prioritising pipes in water distribution networks, based solely upon historic leakages data. In contradiction to distribution pipes, transportation pipes show a limited number of failures. Failures are important indicators to assess the state of a pipe. With a limited number of failures, the effect of failure is often more important than the probability of failure. For Dutch drinking water utility Evides, Spatial Insight tailored risk model SI-Rehab that focuses on distribution pipes, towards the assessment of transportation pipes. SI-Rehab evaluates each segment by multiplying the probability and effect of pipe-failure. The results are risk-scores for each segment.

EVN Wasser has provided Spatial Insight with the GIS-data of the pipes and surrounding networks. The hydraulic model of Rußbachtal area is used to generate hydraulic parameters for the SI-Rehab algorithm, including the calculation of erosion crater diameters.

Part of the results showing the lowest priority pipes.

With different transportation pipe specific calculations, we calculated a risk category for each pipe segment.

Contribution to the organisation’s strategy

Spatial Insight supported EVN to assign the available replacement budget for the replacement of the transportation pipe line to the pipes with highest risk values.

Customer review

Herr Ing. Helmut Brandl has appreciated the work that we have delivered and recommends the approach to other utilities.

MORE INFORMATION

Jan-Kees de Visser
Data scientist hydraulics

"It was exciting to extend our distribution models for transport pipes."

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