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Melting rock models predict mechanical origins of earthquakes


Engineering academics have devised a model that can predict the early mechanical behaviours and origins of earthquakes in multiple types of rock.

The experiments provide new insights into the unobservable phenomena that takes place several kilometres beneath the Earth’s surface under incredible pressures and temperatures. The findings could help researchers better predict earthquakes – or even attempt to prevent them.

“Earthquakes originate along fault lines deep underground where extreme conditions can cause chemical reactions and phase transitions that affect the friction between rocks as they move against one another,” said Hadrien Rattez, a research scientist in civil and environmental engineering at Duke University in North Carolina, USA.

“Our model is the first that can accurately reproduce how the amount of friction decreases as the speed of the rock slippage increases and all of these mechanical phenomena are unleashed.”

Figure 1. The study focuses on the steady state friction co-efficient between rocks. The results for clay and talc are presented as weak phase respectively: (a) red corresponds to a muscovite/halite mixture; orange to a crushed montmorillonite mixture; dark yellow to a quartz powder/bentonite mixture; (b) purple corresponds to quartz as strong phase; blue to calcite; and green to lizardite.

For three decades, researchers have built machines to simulate the conditions of a fault by pushing and twisting two discs of rock against one another.

These experiments can reach pressures of up to 655kg per square inch (psi) and speeds of one metre per second (1m/s), the fastest underground rocks can travel. (For a geological reference point, the Pacific tectonic plate moves at about 0.00000000073 metres per second).

“In terms of ground movement, these speeds of 1m/s are incredibly fast,” Manolis Veveakis, the university’s assistant professor of civil and environmental engineering, added. “And remember that friction is synonymous with resistance. So if the resistance drops to zero, the object will move abruptly. This is an earthquake.”

In these experiments, the surface of the rocks either begins to turn into a sort of gel or to melt, lowering the co-efficient of friction between them and making their movement easier (see Figure 1).

According to the study, it has been well established that as the speed of these rocks relative to one another increases to 1m/s, the friction between them drops. But until now, nobody had created a model that could accurately reproduce these behaviours.

Preventing earthquakes – in theory

In the paper, Rattez and Veveakis describe a computational model that takes into account the energy balance of all the complicated mechanical processes taking place during fault movement.

They incorporate weakening mechanisms caused by heat that are common to all types of rock, such as mineral decomposition, nanoparticle lubrication and melting as the rock undergoes a phase change.

After running simulations, the researchers found their new model accurately predicts the drop in friction associated with the entire range of fault speeds from experiments on all available rock types including halite, silicate and quartz.

Because the model is applicable to many different types of rock, it appears to be a general model that can be applied to most situations, which can reveal new information about the origins of earthquakes.

“The model can give physical meaning to observations that we usually cannot understand,” Rattez said. “It provides a lot of information about the physical mechanisms involved, like the energy required for different phase transitions.”

Veveakis added: “We still cannot predict earthquakes, but such studies are necessary steps we need to take in order to get there.

“And in theory, if we could interfere with a fault, we could track its composition and intervene before it becomes unstable. That’s what we do with landslides. But, of course, fault lines are [32km] underground, and we currently don’t have the drilling capacity to go there.”

The results have been published online in the journal Nature Communications.

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