A fix for pipes before they fail

CSIRO researchers have developed a predictive model for estimating likely failures in underground pipeline networks made from a range of materials.

The cost of repairing and maintaining Australia’s existing water and wastewater infrastructure is estimated at over $130 million each year, so the economic value of being able to predict failures is significant. There are also environmental and social benefits of averting potential failures.

Dr Paul Davis, of the Integrated Urban Water Systems research stream at CSIRO Land and Water, says older pipeline networks have the benefit of historical data that allows utility companies to forecast what is likely to happen in future years.

However, Dr Davis says: “Failure rates in newer materials are relatively low and they have not been in the ground long enough to have collected significant amounts of historical data to support accurate statistical predictions.” 

Dr Davis’s research began in the laboratory where a physical model was developed and tested under conditions replicating a typical installation of an underground pipe. Using short sections of pipe, the model showed high accuracy for predicting pipe failure.

“In the lab, we developed a good understanding of material, degradation, crack growth and fracture aspects of the problem,” Dr Davis says. “However, we had a model that had been developed under well-defined conditions in the lab. 

“If you try to take that across into the field, you have problems. If you have 100km of pipe, you can’t apply this kind of model unless you know the condition along the entire length of the pipe.”

To overcome this, CSIRO has developed a model that uses probability distributions – developed from anecdotal evidence from industry and ”forensic” investigation of failed pipes – to estimate the probable defect size along a pipe, and the probable loading conditions the pipeline experiences.

“The model preserves the details of physical degradation and failure mechanisms that occur in service, and can account for changes in operating loads and the surrounding soil environment,” Dr Davis says.

“However, we can also extrapolate the model to estimate network-wide failure rates, which are more meaningful for utility asset managers.” 

While water companies have embraced the model, it can also be adapted to suit other industries, such as the gas industry. The model was developed as part of two projects, jointly funded by the American Water Works Association Research Foundation.