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New method uses risk aversion to test ability of pipelines to withstand earthquakes

Mohsen Shahandashti. Credit: UTA
Mohsen Shahandashti. Credit: UTA
A researcher at The University of Texas at Arlington (UTA) is developing a new method to test the seismic vulnerability of water pipeline systems – using the principles of risk aversion.

The goal of assistant professor of civil engineering Mohsen Shahandashti’s research is to determine which section of urban water pipeline networks should be replaced to withstand earthquakes.

Shahandashti recently received a grant from the National Science Foundation to develop an algorithm that models the effects of earthquakes on water pipeline infrastructure.

The model will determine how best to use limited funding for infrastructure projects to make pipelines less vulnerable to damage from seismic activity.

Jay Rosenberger and Victoria Chen, professors in the Industrial, Manufacturing and Systems Engineering Department, as well as civil engineering professor Simon Chao are co-principal investigators on the project.

“There is always a risk in rehabilitation projects that you’ll make a wrong decision, especially when you’re working with pipes that have been buried for decades,” said Shahandashti. “The optimisation algorithm that we are creating uses principles borrowed from quantitative finance to solve the problem of which pipes to replace so that communities can make the best decisions possible for the use of their infrastructure funds.”

It is hoped that the research will allow cities to more accurately predict where pipelines are most vulnerable, so they can be repaired and replaced before an earthquake event to avoid water outages.

“Clean drinking water is a necessity for our communities, and anything we can do to ensure that people in earthquake-prone areas will see limited interruptions to their access to water will make those cities more liveable,” added Civil Engineering Department chair Ali Abolmaali. “This project combines decision science and infrastructure assessment in a truly novel way, and if Dr. Shahandashti’s algorithm works as well as his early results indicate it might, the research could have a far-reaching impact on how cities maintain their water pipelines.”
Mohsen Shahandashti. Credit: UTA