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Predicting the risk of dam failure

Find out how grid computing is helping to predict the effects of a toxic spill in a tailing dam...

Plan view of the Żelazny Most tailing dam area. The slope of the dam is represented in brown. Each of the five failure modes results in different contamination areas, from 2.0 to 5.5 km2 (number in brackets). The extent of the contamination flow is represented in blue for each scenario.

Poland's Żelazny Most tailing dam was built in the late 1970s as a final resting place for the contaminated wastes produced by the Lubin, Rudna and Polkowice-Sierszowice copper mines in the south-west of the country. As of 2012, the dam spreads across 14km2 of countryside and receives about 80,000 tonnes of clay waste material per day, growing more than a meter in height every year.

Dam failure at this point would mean 10 million cubic meters of contaminated waste flooding the valley, with tragic consequences for the environment and for the health of local people. The key to prevent disaster is to understand what could happen in the event of a toxic spill.

And the key to that is grid computing.

Anatomy of the Żelazny Most tailing dam

Stella Arnaouti, a civil engineer based at the Aristotle University of Thessaloniki (AUTh) in Greece, studied the risk of a slope failure at the Żelazny Most dam. The study helps to assess the validity of a tool used for risk assessment, which was developed as part of the IRIS research programme (Integrated European Industrial Risk Reduction System). The goal was to determine the extent of the contaminated area in the event of a toxic spill.

The Żelazny Most dam can be subdivided into 116 geological sections around the perimeter. Each section is made up of a complex sequence of individual soil layers with specific soil density, effective friction angle and soil cohesion - the soil factors that control slope failure.

Stella compiled the results of cone penetration tests to estimate the mean value, the variability of soil strength parameters (effective friction angle and cohesion) and the seismic acceleration measurements. This allows her to determine the mean value and the variability of the seismic acceleration applied to the dam.

"This means [there are] 15,000 different sets of input parameter values based on their variability," Stella explains. "Then I assessed how each one of the 116 sections reacted - as you can imagine, for some sets, the dam failed and contaminated slurries were released." Stella's work identified different failure modes - possible ways for the dam to fail and spill toxic slurries.

How far can the contamination go?

Having found how the tailing dam can fail, Stella then assessed the risk of a spillage by determining the total area of contamination for each failure mode. For this task, Stella recruited the help of Paschalis Korosoglou and the grid team at the AUTh computing centre. Stella used grid computing to simulate the slurry flows with software called Flow-3D. This allowed her to model the contamination spill in three dimensions, covering an extensive area of 100 km2. "Without the grid infrastructure, I wouldn't be able to apply a 3-dimensional flow model to my study," she explains.

The simulations showed that "the consequences of a slope failure at the Żelazny Most tailing pond vary considerably with different failure modes," says Stella.

The conclusions, published as part of the IRIS project report, highlight how "risk assessment can be a valuable tool, since it helps you to understand the different ways your structure may behave," Stella explains. This in turn is very useful to help plan disaster responses and to minimise damage in case of dam failure.

This article was originally published on the EGI website.

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