“We have derived an analytical solution for the propagation of sound waves from slender faults being displaced upwards, then applied an inverse approach to calculate the main properties of the fault and its movement — such as location, length, width, orientation, duration, speed, and time of eruption,” Dr. Usama Kadri, from Cardiff University’s School of Mathematics, told Digital Trends. “Practically, the solution allows us to analyze hydrophone [underwater microphone] recordings and calculate the main properties of the fault in near-real time.”
At present, tsunami early warning systems involve floating devices that measure pressure changes in the ocean. This isn’t a perfect solution, since the large number of flotation devices makes it extremely costly. Because it relies on physical contact with the tsunami in order to register a possible wave, it’s also not useful if the device is located too close to shore — since it would provide only a few extra minutes or seconds of warning.
The Cardiff University system, on the other hand, analyzes naturally occurring acoustic gravity waves (AGWs) generated in the deep ocean following a tsunami trigger event such as an underwater earthquake. Because these AGWs travel more than 10 times the speed of a tsunami wave, they can be far more effective in offering a useful alert.
“We’re currently analyzing other main properties under actual scenarios, and developing an efficient tsunami model that can run in parallel to the inverse solution, to maximize efficiency and warning time,” Kadri said. He noted that the team would consider commercializing the technology, although this would only be done “if it will not act as a barrier, at whatever level, in front of the main objective of our work: to create an efficient tsunami warning system to protect lives globally and invariably.”
A paper describing the work was recently published in the Journal of Fluid Mechanics.
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